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H.E.R.O.’s Journey in Tech (31 January 2019) – SM Entertainment Enters Into Strategic Partnership Agreement With China’s Tencent Music + What If Unhappiness Contains The Secret To Happiness?

H.E.R.O.’s Journey in Tech (31 January 2019) – SM Entertainment Enters Into Strategic Partnership Agreement With China’s Tencent Music + What If Unhappiness Contains The Secret To Happiness?

Companies

  • SM Entertainment Enters Into Strategic Partnership Agreement With China’s Tencent Music (Soompi); Tencent has built a portfolio of music app sthat have fandom culture at their core; whether that be the live streaming, social features and in-app gaming of Kuwo, virtual tipping on KuGuo Live or VIP passes to get access to special virtual gifts in karaoke app Quanmin K Ge (We Sing). (MIB)
  • Zuken to Acquire Vitech; Vitech Corp.’s GENESYS product is a MBSE software tool that incorporates the key components of building a complex system involving people, processes, data, and documentation (TL)
  • Chat app Line’s mobile payment service is getting its own Visa card (TC)
  • Sam Tsai: The pivotal figure behind Taiwanese e-commerce giant PChome’s entry into Thailand’s e-commerce market (e27)
  • Foxconn reconsidering plans to make LCD panels at Wisconsin plant (Reuters)
  • Zomato in talks to sell UAE biz to German co for $200m; Info Edge, an early backer which owns around 28% of the company, called the battle with Swiggy “a hugely capital-consumptive game” (TOI)
  • Bravura Solutions becomes first tech firm to join GRiD (CM)

BATTSS – Baidu, Alibaba, Tencent, TSMC, Samsung, Softbank

  • Alibaba growth hits 3-year low as shoppers trim big-ticket buys (Nikkei)
  • Even with one more title on China’s gaming whitelist, Tencent still has its cash-cow titles in limbo (KRA)
  • Tencent to power Hong Kong startups amid its shift to enterprise (Technode)
  • SoftBank’s Massive Debt Burden Looks Worse Than It Actually Is (Bloomberg)

FAANNMG – Facebook, Amazon, Apple, Nvidia, Netflix, Microsoft, Google

  • Apple’s new developer guidelines signal that scammy subscription apps’ time is up (TC)
  • Apple reaches ‘defining moment for Cook’ amid weakening iPhone demand; The company didn’t forecast how many iPhones it will sell, something Apple has done since the product first hit the market in 2007 (JT); If Apple is serious about becoming a services company, it should truly go for it (qz)
  • Apple Stock Is Up. Don’t Buy the Suppliers, Says Analyst. (Barron’s); Apple Is Planning 3-D Cameras for New iPhones in AR Push (Bloomberg)
  • Facebook’s Good Quarter Can’t Hide Tough Ones Ahead; It must leverage news feed and Instagram fans into new offerings and figure out how to monetize them. (Bloomberg); Facebook quietly blocked tools that let people see how its ads are targeted (qz); By defying Apple’s rules, Facebook shows it never learns (Wired); Apple bans Facebook from tech tools for tracking teen browsing habits (Reuters)
  • Microsoft’s Azure revenue growth slows, shares fall (Reuters); Microsoft Sales Meet Estimates; Cloud Concerns Hit Shares (Bloomberg)
  • Google disables iPhone app that studied users’ digital habits (Reuters)
  • Why the Netflix Price Hike Should Worry Investors (Barron’s); How Netflix came to dominate Hollywood (Edge)

Asia Tech & Innovation Trends

  • China’s Online Tutor Startup VIPKid Is Seeking $500 Million at $6 Billion Valuation; The startup saw its losses grow nearly fourfold over a year to almost RMB 1.2 billion ($173 million) in 2017 (TN)
  • China unveils trading rules for new hi-tech board, paving way for bold new market to compete with New York, Hong Kong (SCMP)
  • Passengers could take an autonomous train to Beijing’s new airport starting September (KRA)
  • It’s time to pay serious attention to TikTok (TC); World’s most valuable start-up ByteDance slashes ‘lucky money’ for Year of the Pig as founder warns of challenging 2019 (SCMP)
  • As carmakers go all in for tech, Akebono and suppliers left behind; Toyota and peers demand price cuts to free up cash for future vehicles (Nikkei)
  • Paytm enters hotel booking business, buys NightStay (ET)

Global Tech & Innovation Trends

  • Robot valets may soon park your car at this London airport (CNN)
  • AI could run your life in 2030, as consumers look to tech to make lives easier (TODAY)
  • A Tech Firm Far From Silicon Valley Churns Out Billionaires; Shares of payments upstart Adyen have almost tripled since IPO (Bloomberg)
  • AI Tradeoff: Accuracy or Robustness? (EE Times)
  • Home improvement platform Houzz lays off 180, reportedly gears up for public listing (TC)
  • As AMD Stock Soars, CEO Says Its ‘Superior’ Chips Will Win in 2019 (Barron’s)
  • PayPal stock falls after outlook miss, but CEO says Venmo has hit a ‘significant transition point’ (MW); PayPal Sales Miss Estimates for the First Time Since 2015 (Bloomberg)

Life

  • What If Unhappiness Contains The Secret To Happiness? (Medium)
  • The secret of great learners: Focus on the process, not the outcome (MT)
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H.E.R.O.’s Journey in Tech (30 January 2019) – The co-founder of Automation Anywhere says that a professional skilled in robotic process automation (RPA) can earn up to a 30-percent higher salary; Accenture to Sell RPA Software That Helped It Cut 40,000 Jobs

H.E.R.O.’s Journey in Tech (30 January 2019) – The co-founder of Automation Anywhere says that a professional skilled in robotic process automation (RPA) can earn up to a 30-percent higher salary; Accenture to Sell RPA Software That Helped It Cut 40,000 Jobs

Companies

  • Huawei Is Blocked in U.S., But Its Chips Power Cameras Everywhere; The law also specifically mentions Chinese surveillance camera makers Dahua and Hikvision as companies that can’t supply the U.S. government (Bloomberg)
  • USI Planned to Sign a Contract to Invest in Huizhou Daya Bay New Plant Project (AO)
  • Line.me surpasses 1 million users; The app was founded by Lensa Corp. – a joint venture between En-Japan Inc. (51 percent) and Line Corp. (49 percent) – in Oct. last year (AIM); Listings from Japanese tech-focused staffing firm En-Japan Inc. are now being indexed by Google for Jobs in a bid to reach a broader audience. (AIM)
  • Kakao mulls acquiring Nexon (Investor)
  • Holtek net profit rises 15% on foreign-exchange gains (TT); Holtek enters wireless headset supply chains of China handset vendors (Digitimes)
  • Afterpay challenger Splitit up 90 per cent on first day of trade (AFR)

BATTSS – Baidu, Alibaba, Tencent, TSMC, Samsung, Softbank

  • Alibaba’s alternative to the app store reaches 230M daily users (TC)
  • Tencent works with Hong Kong’s science park to spur local fintech development (SCMP)

FAANNMG – Facebook, Amazon, Apple, Nvidia, Netflix, Microsoft, Google

  • Amazon and Microsoft Stock Will See Long-Term Gains From Cloud Trends (Barron’s)
  • The Endgame for LinkedIn Is Coming for Microsoft (Medium)
  • Nvidia is latest sign that the cloud boom is dying (MW)

Asia Tech & Innovation Trends

  • Shenzhen-based Hive Box says 5% of all parcels delivered by couriers in China end up in its smart lockers (KRA)
  • Behind the rise of China’s smartphone brands lies growing unease over country’s tech gains (SCMP)
  • How China acquired mastery of vital microchip technology; The rise of NavTech shines light on Beijing’s methods in cultivating semiconductor winners (FT)
  • Japan Display’s brief success is familiar national champion’s tale; Key iPhone supplier hobbled by low-cost competition and questionable investment decisions (FT)

Global Tech & Innovation Trends

  • SAP job cuts prove harsh realities of enterprise transformation (TC, MW)
  • Researchers take step closer to creating tech that can read minds; Columbia University team constructed clear synthetic speech by processing human brain activity (FT)
  • How AI Is Transforming The Next Generation Of Vehicles (Forbes)
  • The co-founder of Automation Anywhere says that a professional skilled in robotic process automation (RPA) can earn up to a 30-percent higher salary (Forbes); Accenture to Sell Software That Helped It Cut 40,000 Jobs (Bloomberg)
  • FanAI buys Waypoint Media to better track fan engagement for streaming monetization (TC)
  • Slack now has more than 10 million daily active users (TC)
  • WeWork could challenge Starbucks in China with new on-demand service (TC)
  • Waymo Met With More Than 12 Carmakers in 2016 on Driverless Tech (Bloomberg)
  • Square Stock Is Downgraded on Worry Over Slowing Growth (Barron’s)

Life

  • The Single Greatest Error (Batnick)

H.E.R.O.’s Journey in Tech (29 January 2019) – AI loan screening for Japan regional banks to take only seconds + Getting Ahead By Being Inefficient

H.E.R.O.’s Journey in Tech (29 January 2019) – AI loan screening for Japan regional banks to take only seconds + Getting Ahead By Being Inefficient

Companies

  • 111 Inc plans to help China’s generic drug makers better compete by slashing marketing and distribution costs; China’s largest online pharmacy has also signed a deal with Eli Lilly, giving the US pharmaceutical giant access to its cloud computing solution (SCMP)
  • Tencent-backed Maoyan prices Hong Kong IPO at lower end, raises $250 million (Reuters)
  • Xiaomi’s Rout Throws a Spotlight on Hong Kong’s Expiring Lockups (Bloomberg)
  • ARQIS has advised Hamamatsu Photonics Deutschland on the acquisition of a minority interest in Menlo Systems, a leading developer and worldwide supplier of instruments for precision metrology (PEW)
  • Restaurants in Japan boost delivery services ahead of tax windfall; Relief measure cooks up demand for Uber Eats and local services; Demae-can, the food delivery platform operated by Yume no Machi Souzou Iinkai, is already seeing increased business (Nikkei)
  • Kids contents creating company CarrieSoft is planning to get listed on the second-tier KOSDAQ market in 2019. The company’s unique business model of making revenue by creating YouTube videos for kids, selling intellectual property rights and producing toys and goods with the characters used in its contents, will be evaluated as its potential technology that can grow the company. Established in 2014, CarrieSoft’s sales in 2017 reached 6.3 billion won (US$5.65 million), while posting 400 million won operating profit. Industry insiders estimate that it sales last year surged to around 10 billion won (Investor)
  • ASMedia lands mainstream PCIe chip design orders from AMD (Digitimes)
  • Automotive-centric semiconductor players to drive tech sector (Edge)
  • DBS suspends coverage of Y Ventures after restatement of 1H18 results on admin errors; Group now expects FY18 loss (Edge)

BATTSS – Baidu, Alibaba, Tencent, TSMC, Samsung, Softbank

  • Can WeChat defend its social media predominance by blocking its competitors? (SCMP)
  • Alibaba Shows Signs of Strain as China’s Economy Shudders (Bloomberg)
  • TSMC chip output for Nvidia and Huawei hit by defective chemical (Nikkei)

FAANNMG – Facebook, Amazon, Apple, Nvidia, Netflix, Microsoft, Google

  • Facebook Watch Isn’t Living Up to Its Name; The company’s lackluster video tab still has a lot to prove to both viewers and advertisers. (Bloomberg)
  • Google, Amazon seek foothold in electricity as home automation grows (Fox)
  • Why a tiny screw caused big problems for Apple (Age)
  • An Apple Videogame Subscription Service Makes Sense. Will It Happen? (Barron’s)
  • Chipmakers Slide as Nvidia’s Outlook Underlines Growth Fears (Bloomberg); Nvidia Short-Sellers Reap $457 Million in Monday’s Rout, S3 Says (Bloomberg)

Asia Tech & Innovation Trends

  • China’s work ethic stretches beyond ‘996’ as tech companies feel the impact of slowdown (SCMP)
  • AI loan screening for Japan regional banks to take only seconds (Nikkei)
  • Japanese officials will target millions of IoT devices to help secure the Olympics (TNW)
  • Taiwan firms gearing up for OLED market boom (Digitimes)
  • Grab moves into video content with Hooq (TIA)

Global Tech & Innovation Trends

  • The four types of music subscription models in 2019 (MBWW)
  • Kite raises $17M for its AI-driven code completion tool (TC)
  • Scout24’s market value fell sharply last year after lawmakers suggested that property vendors should pay real estate agents’ commissions instead of passing them on to buyers (Bloomberg)
  • The BuzzFeed Lesson (Stratechery)
  • Eureka Park: Startup teams present wide-ranging AI engines targeting diverse applications (Digitimes)
  • Humans Question Their AI-Based Future; Smart machines are now being applied to activities requiring intelligence and cognitive capabilities (WSJ)
  • Wayfair Stock Can Rise Another 30%, Says Analyst (Barron’s)
  • This Analyst Sees Grubhub Stock Rising 60% (Barron’s)
  • Dropbox to Acquire E-Signature Software Company HelloSign; Deal is worth $230 million, expected to close this quarter (Bloomberg); Dropbox Drops $230M To Get Into The Digital Signature Game (CB)
  • Snapchat weighs what was once unthinkable – permanent snaps (Reuters)

Life

  • Getting Ahead By Being Inefficient (FS)
  • What Charles Darwin can teach us about beating creative block (qz)

H.E.R.O.’s Journey in Tech (28 January 2019) – Tencent Music Co-Presidents Cross Into Billionaire Terrain + Charlie Munger on learning to be a great investor

H.E.R.O.’s Journey in Tech (28 January 2019) – Tencent Music Co-Presidents Cross Into Billionaire Terrain + Charlie Munger on learning to be a great investor

Companies

  • Tencent Music Co-Presidents Cross Into Billionaire Terrain (Forbes)
  • iFlytek: China looks to built ‘smart courts’ with AI; The platform can recognize verbal commands to display relevant information. It can also transcribe speech while identifying speakers. (Technode)
  • As Demand Stagnates, China LED Lighting Giant Feels the Heat (Bloomberg)
  • Sensor maker Cub Elecparts to integrate radar systems subsidiary (TT)

BATTSS – Baidu, Alibaba, Tencent, TSMC, Samsung, Softbank

  • ByteDance and Tencent squabble over social media “clean-up” (KRA)

FAANNMG – Facebook, Amazon, Apple, Nvidia, Netflix, Microsoft, Google

  • The fall of Facebook has only begun. The platform is broken and neither human nor machine can fix it. Even after losing roughly a third of its market cap, it still may prove one of the great shorts of all time. (Medium)
  • Amazon is everywhere, and companies can’t stop talking about it (qz)
  • Amazon to ‘revolutionise’ shopping with ‘virtual changing room’ app (Telegraph)
  • Google, Amazon Seek Foothold in Electricity as Home Automation Grows; Tech companies look to expand their reach, reap consumer data as smart-home ecosystem expands (WSJ)
  • Google Memo on Cost Cuts Sparks Heated Debate Inside Company (Bloomberg)
  • Steve Jobs Never Wanted Us to Use Our iPhones Like This; The devices have become our constant companions. This was not the plan. (NYT)

Asia Tech & Innovation Trends

  • Ofo’s demise highlights risks of Chinese tech model; How subsidising consumers to win market domination bled bike-share service dry (FT)
  • Why do people in China spend so much on livestreamers? (TIA)
  • Autonomous service vehicles gaining ground (China Daily)
  • Drone maker DJI eyes enterprise business in transformation from hardware maker to platform operator (SCMP)
  • China created a unicorn every 3.8 days in 2018 (SCMP)
  • Asian tech suppliers brace for prolonged downturn (Nikkei)
  • Japanese AI startup Cinnamon closes series B round with $13.7M in funding (Bridge)
  • Going walletless: Korea’s mobile payment market diversifies as competition grows (Investor)
  • Korean gaming industry faces deeper Chinese invasion (Investor)
  • India’s Ola slashes its budget for Foodpanda (TIA)
  • Singaporean online parenting startup theAsianparent to raise new round led by Fosun (KRA)
  • Five of the eight films nominated for the best picture Oscar for 2019 last week were made using products from a relatively unknown Australian company. (Age)

Global Tech & Innovation Trends

  • Another tech bubble could be about to burst; We are in the late stages of a credit cycle, with too much money chasing too little value (FT)
  • Philips lights on AI to target growth in healthcare; Predictive data from devices will be used to avert medical crises (FT)
  • How AI, blockchain, and wearables are changing the face of healthcare (TNW)
  • Airbnb acquires Denmark’s Gaest to expand in bookings for meetings and offsites (TC)
  • A New, Faster Approach To Data Science And Machine Learning (Forbes)
  • Is The Direct-To-Consumer Bedding Business Turning Into A Bad Dream? (Forbes)
  • New Job for Robots: Taking Stock for Retailers; As retail supply chains get more complicated, stores are looking at mobile data collection to track inventory levels (WSJ)
  • Munchery Becomes the Latest Casualty of the Food Delivery Shakeout; Employees in tears, leftover food and unpaid bills marked the final days of a once-buzzy on-demand darling. (Bloomberg)
  • BuzzFeed, and the bursting digital media bubble (Age)

Life

  • Charlie Munger on learning to be a great investor. “The trouble with the Wrigley Gum-type investments is that everybody can see that they’re wonderful businesses. So you look at it and you think, My God! The thing’s at eight times book value or something. And everything else is at three times book value.’ So you think, ‘I know it’s wonderful, but is it wonderful enough to justify that big a premium?'” The ability to answer such questions explains why some people are successful investors and others are not. “On the other hand, if it weren’t a little difficult, everybody would be rich,” Munger insisted. (VIW)
  • In Search of the Canary Tree: What a Disappearing Ancient Forest Can Teach Us About Resilience and Grace in a Changing World (BP)
  • US$369.6 million in defaults at apparently cash-rich firms expose flaws in mainland Chinese auditing practices (SCMP)
  • SGX to get tougher on auditing of listed companies with proposed new rules (ST); SGX RegCo teams up with professional body of valuers to tackle problem of questionable valuations (Edge)

FRONTEO (TSE: 2158), Asia’s Leading Legaltech Innovator Powered by Artificial Intelligence (AI) & Expanding AI Solution Into Healthcare and Business Intelligence (BI) – H.E.R.O. Innovators Insights from CEO Masahiro Morimoto | H.E.R.O. HeartWare | 28 January

Can artificial intelligence (AI) learn from the tacit knowledge (experience and intuition that is difficult to verbalize) of human experts from attorneys and marketers to doctors and researchers and analyze massive volume of data that requires effective judgment to become ever more accurate and faster?

These are some of actual high-value problems that this “intuitive” AI has already helped solve:
(1) In finding relevant legal and forensic evidence from a huge volume of complex documents and data in multi Asian languages within limited time in accordance with the judgment criteria of attorneys for disclosure in the review process, which is the most expensive part of the U.S. and cross-border litigation cases that typically account for 70% of the costs. This “intuitive” AI can review at nearly four thousand times the speed and with 30% greater accuracy than an expert human reviewer, reducing costs to one-tenth;
(2) In compliance checks at a growing number of major banks to judge whether financial products are sold appropriately by the salesperson to determine that they do not churn, or make their customers frequently buy or sell assets instead of recommending financial instruments that matches the knowledge, experience, asset situation and investment purposes of customers, based not only on the customer profile but importantly also on the content of the incident record with the customer stated by the salesperson. This “intuitive” AI increased the extraction efficiency of conflict possibilities by about 15 times, helping to reduce litigation risk by early follow-up;
(3) In preventing the risk of patients falling during hospitalization by analyzing the unstructured data and free-form writing in electronic medical records that record the tacit knowledge of doctors and nurses to understand the whole of a patient. This “intuitive” AI notices and learns the intuition and experience of doctors and nurses to improve the prediction accuracy by about 50% compared to the conventional methods such as Morse Fall Scale and STRATIFY, benefiting the 1.32 million hospitalized patients in Japan;
(4) In providing precision medical treatment for each cancer patient by comprehensively analyzing genetic abnormalities in cancer patients and research methods for integrating and analyzing patient diagnostic data such as genome analysis information, including an information support system that lets student doctors learn how experts select medical information and papers according to the individual cancer patient, benefiting the 1 million cancer patients in Japan;
(5) In chronic pain diagnostic support, since chronic pain is difficult to objectively evaluate and depends on the experience and subjectivity of the doctor and can be complicated by a combination of body abnormalities (biological factors) and stress environments (psychological and social factors), and the time and labor cost for examining one patient is very high as a result of the multidisciplinary examinations required. This “intuitive” AI learns from the tacit knowledge in diagnostic and therapeutic skills accumulated from the multidisciplinary medical care provided by the team of specialized orthopedic surgeons, anesthesiologists, psychiatrists, nurses, physicists, therapists, clinical psychologists working together on the clinical practice of chronic pain to make accurate and fast diagnosis and transition to appropriate treatment leading to pain improvement as soon as possible, benefiting the 20 million patients with chronic pain in Japan’s super aged and stressed society;
(6) In patent search and analysis to smooth patent research essential for product development and patent application by analyzing intellectual property publications, documents and technical trend surveys investigating the latest technical information. This “intuitive” AI, developed jointly with and endorsed by Toyota Technical Development since 2015, learns the judgement made by an expert in extracting similar patents since the traditional search method is a special skill by itself and and not everyone can do it, speeding up the patent search exponentially, and the companies subscribing to this Patent Explorer software-as-a-service on a recurring basis has jumped 2.5 times year-on-year as of Nov 2018;
(7) In speeding up discovery of new drug candidate compounds for researchers engaged in the R&D of novel drugs at pharmaceutical companies. This “intuitive” and patented AI learns the tacit knowledge from the hypotheses of the researcher to search and investigate relationships with diseases that are likely related and drugs that change similar genes, target gene networks, and can also emerge new diseases that are closely related to specific compounds, as well as realizing statistical significance difference tests essential to evidence based medicine.

This week, we highlight the under-the-radar listed Asian exponential innovator FRONTEO (TSE: 2158) who is Asia’s leading legaltech innovator powered by AI and expanding its AI solution “KIBIT” into healthcare and business intelligence as a SaaS (Software-as-a-Service) recurring revenue model for non-legal clients. Guided by the mission to illuminate the darkness lurking in data by securely identifying the risks and opportunities buried in records by utilizing technology, FRONTEO (formerly called UBIC) was founded in Aug 2003 by Masahiro Morimoto as a legaltech company supporting eDiscovery (electronic evidence disclosure) and digital forensic services for clients involved in US and international cross-border litigation, corporate investigations and intellectual property disputes. The data analytics platform Lit i View with “predictive coding” technology which supports multiple Asian languages (China, Japan, Korea) was developed in 2012 and was further enhanced with the AI engine KIBIT developed in Nov 2015 that is leveraged upon to develop the AI Solution business for non-legal clients. FRONTEO’s KIBIT series had acquired the number one market share of 26.8% based on sales value in the domestic natural language analysis market for 2016 and 2017 in the independent ITR survey announced on 11 Dec 2018, which is nearly doubled that of the 13.9% share held by the second place vendor. KIBIT uses the proprietary and unique “landscaping” AI technology to learn the “tacit knowledge” (experience and intuition) of human experts and, unlike all other AI technologies, KIBIT requires only small volume of data for effective machine learning to produce good quality output and solve customers’ problems.

This is unique and important because (1) KIBIT can learn the tacit knowledge and judgment criteria of human experts such as attorneys which is not always available in large data quantities, and (2) many artificial intelligence in the world aims to become smarter by analyzing big data, but there is a need to “teach” the artificial intelligence using a lot of data so that it can actually make effective judgment at the business site. However, there are many companies that do not have adequate data for teaching and practical application is difficult if machine learning does not proceed. KIBIT deftly identifies the specific features of a small volume of data and makes judgement that can be consistently applicable to a larger volume of unknown data, functions in a manner akin to landscaping, or visualizing a complete scene from a narrow field of view. As FRONTEO CTO Takeda Hideki comments, “A cut out from a large landscape picture would show artistic expressions depending on where the cut was made. KIBIT can detect such sense of beauty and learn from it intelligently.”

FRONTEO’s business model is a mix of project-based revenue (legaltech business) and recurring revenue (AI Solution business) with improving profitability in overall TTM (trailing twelve months) operating margin of 8.9%, ROE (= EBIT/ Equity) of 22% and ROA of 7.6%. The AI Solution business turned profitable in 3Q FY18/03 after hitting an inflection point in moving from PoC (proof-of-concept) for its clients to the full-launch stage and has amassed a wealth of solutions and cases to aid marketing; sales jumped 1.4-fold yoy and clients grown 1.8 times yoy to more than 121 customers as at 2Q FY2019 (Sept 2018). FRONTEO’s AI Solution business serves clients in the financial & healthcare industry/ “KIBIT Knowledge Probe” (MUFG Bank, Yokohama Bank, Resona Bank, Aeon Bank, SMBC Nikko Securities, Mitsubishi UFJ Morgan Stanley Securities; Daichi-Sankyo, LITALICO), compliance/ ”KIBIT Email Auditor” (Toyo Tires, Innolux, Evergreen Marine), and patent analysis/ ”KIBIT Patent Explorer” (Denso, Kikkoman, Sapporo, Kuraray, Showa Denko, Toray, Toyobo). FRONTEO launched its second AI engine “Concept Encoder” in Dec 2018 for the healthcare industry in drug discovery and clinical trials. Whereas KIBIT excels in natural language processing, Concept Encoder can analyze data other than language, including symbols and gene expression. The AI Solution business is expected to contribute 13% and 7.1% of sales and operating profit respectively in FY2019/03. In its new medium-term plan announced in May 2018, FRONTEO expects its AI Solution business to increase in sales from 1.8bn yen in FY2019/03 to 5.8bn in FY2020 and 11.8bn yen in FY2021, and contribute 31.2% of operating profit in FY2020 (645m yen) and 57.1% in FY2021 (2.418bn yen).

In its legaltech business, FRONTEO has far superior eDiscovery support tools in which Lit i View is the only platform that supports Asian languages without the garbling problem and the only one that offers end-to-end eDiscovery services that combines a workflow system plus AI analytical tools KIBIT that increases the efficiency and accuracy of the document review process, a critical aspect of eDiscovery that accounts for 70% of the cost. Lit i View platform has a review management dashboard where clients can have up-to-the-minute metrics on review progress, which includes a heat map within Lit i View that provides a detailed snapshot of reviewer progress and productivity and enables course corrections as needed. Most litigation cases in the US do not reach trial (examination of facts in a public court). Usually, a settlement is reached during pre-trial. However, unlike in Japan, in the US the victor of a settlement is largely determined by the discovery process, wherein evidence is presented to each side. Therefore, discovery plays a key role in ensuring that the terms of a settlement are as favorable as possible. As such, discovery can determine the outcome of litigation and the discovery process account for 70% of the cost of litigation.

However, despite its overwhelming technological superiority, FRONTEO has faced great difficulties over the years in trying to break through the established practices of US litigation cases that involve Asian companies, its main market, and grow its market share from the current 3%, as well as achieve a stable targeted operating profit margin of 10%. eDiscovery providers are often selected by the Asian companies’ US subsidiaries or by US attorneys, not by Asian companies themselves. In other words, when a lawsuit is filed in the US, Asian companies have a strong tendency to leave the selection of lawyers and other service providers to their local subsidiary. US lawyers tend to leave the choice of eDiscovery providers to their litigation support teams but the attorneys have a powerful sway in the vendor decision.

Thus, unlike the other AI innovators we have investigated whose solutions were readily and rapidly adopted by their clients to solve high-value problems, FRONTEO was an odd case that stood out because the legal industry was particularly resistant to utilizing AI despite its effectiveness since the hours spent can be billed back to the clients and the attorneys make or influence the decisions on the IT vendor based on “relationships”. In short, when FRONTEO targeted its powerful AI legaltech solution to the end corporate clients in Asia involved in litigation suits and to the US litigation support team, it neglected its ultimate client – the US attorneys – and lost the war.

A positive inflection point in its legaltech business could be near after the completion of structural business reforms at its US subsidiaries in FY18 helped FRONTEO to win several large Asian (including Japanese) clients in 1H FY2019 and the management comments that “We are finally able to do what we’ve been really wanting to do” and expects a strong 2H pipeline with several more orders. After 15 years since its founding in 2003, FRONTEO finally established a global legal headquarters in US in April 2018 with global offices under direct control of this HQ to strengthen the overall sales structure and better build relationships with US law offices, strengthened internal controls, and undertook actions to curtail unprofitable projects in the US.

“We want to protect enterprises that are not able to find the necessary information for their litigation battles and are at a disadvantage due to their poor data analysis technology. We want to identify and deliver the right necessary information to each patient among the flood of information. Such kind of passion enriches our AI technologies and medical services every day. Through these activities, we are redefining ‘Bright Value’, which we want to make a reality, as ‘making our information society fairer by securely identifying the risks and opportunities buried in records’ using the data analysis knowhow and highly-advanced AI technologies we have developed.” – FRONTEO CEO Masahiro Morimoto

Ultimately, beyond the glaring business model weaknesses/risks (and assessing potential positive inflection point) and overwhelming technological strengths/opportunities for FRONTEO as we go deeper beyond the usual top-down thematic approach to separate the true innovators and the swarming imitators, the most critical test is to distinguish between the devoted Missionaries forging a purpose and the promotional Mercenaries opportunistically worming themselves into riches-recognition – to focus on the H.E.R.O. innovators who are governed by a greater purpose in their pursuit to contribute to the welfare of people and guided by an inner compass in choosing and focusing on what they are willing to struggle for and what pains they are willing to endure, in continuing to do their quiet inner innovation work, persevering day in and day out.

We are thankful as always to be invited by John Mihaljevic, Chairman of MOI Manual of Ideas Global, to speak at the upcoming Asian Investing Summit 2019 to take place live online on April 10-11. We look forward to sharing with the MOI community of investors about the distinctive value opportunity in a selected group of under-the-radar Asian SMID-cap exponential innovators who generate high profitability and positive free cashflow in solving high-value problems for their customers and society with a higher sense of purpose, as well as the learning insights from our investment mistakes as the world shifts structurally from Value 2.0 (the world where Charlie Munger nudged Warren Buffett from the Ben Graham-style of statistically cheap net-net asset plays in Value 1.0 towards Value 2.0 in qualitative investing in outstanding companies at reasonable prices) to Value 3.0 where disruptive innovation forces sweeping across industries create ever more “value trap” losers and a selected under-the-radar group of winners with exponential edge.

Our recent article on “GA technologies (TSE: 3491), ‘Japan’s Amazon in Real Estate’ Powered by Artificial Intelligence to Profitability” was also featured on a new magazine publication “Becoming Human: Artificial Intelligence“. The magazine explores the latest news and information on Artificial Intelligence, Machine Learning, Deep Learning, Big Data and what it means for Humanity, and article contributors include Kai-Fu Lee, CEO of Sinovation Ventures (创新工场) and former President of Google China. Thus far, of the 58 entrepreneurs and CEOs whom we had highlighted in our weekly research brief HeartWare, 25 are in our focused portfolio of 42 HERO Innovators while the rest are in our broader watchlist of 200+ stocks.

Starting 2 January 2019, we are now located at 182 Cecil Street, Level 17 of the Frasers Tower building where Microsoft is one of the anchor tenants. Frasers Tower is located between the Bangkok Bank building and the Telok Ayer Chinese Methodist Church and is near the Amoy Street hawker food center. We welcome you to visit us over a warm cup of afternoon coffee at our new office on any day.

Our emotional labor of love over the past months in sharing openly our research ideas (to battle-test our ideas by critiques and avoid blindspots in investing) and setting up the proper regulated UCITS fund structure to protect investors’ interests has deepened our conviction for the positive change that we will make together with H.E.R.O. – and we are getting closer to giving birth in February 2019 to H.E.R.O., the only Asia SMID-cap tech-focused fund in the industry and guarding investors’ interests in the regulated UCITS fund structure with daily NAV & daily liquidity and no exit fees.

If you are not moving forward in this exponential world, you are going backwards. If you want to join us at the leading edge of opportunity, if you identify yourself in the values and bigger sense of purpose in H.E.R.O., or you wish to tell from your heart to your most important person, son, daughter, wife, husband, or best friend that you are a farsighted and thoughtful explorer in the H.E.R.O.’s Journey participating in the long-term exponential growth of a selected group of outstanding entrepreneurs, standing up for the embracement of the human spirit, please contact us via email or WhatsApp at +65 9695 1860. Thank you very much for your patience and support and we look forward to growing exponentially with you as we explore the H.E.R.O.’s Journey together.


“The reason I set up FRONTEO in Aug 2003 is rooted in the mission to solve the problem of Asian companies fighting litigation measures globally, especially in the litigious US society where they are incurring huge costs. With the desire to protect companies in Asia including Japan, and as a result of thoroughly pursuing technology in a demanding environment where high precision is needed in a short period of time for international litigation support and for fraud investigation, we have created a unique proprietary artificial intelligence engine called KIBIT. KIBIT learns the tacit knowledge (experience, intuitive sense, know-how and subtleties of human thoughts that is difficult to verbalize) of human experts and can predict the future from the same feeling as human beings. We discovered that this artificial intelligence can be applied in new business areas in healthcare, business intelligence and digital communications to further solve social issues, in addition to the foundation of our business in legaltech. We want to protect enterprises that are not able to find the necessary information for their litigation battles and are at a disadvantage due to their poor data analysis technology. We want to identify and deliver the right necessary information to each patient among the flood of information. Such kind of passion enriches our AI (artificial intelligence) technologies and medical services every day. Through these activities, we are redefining “Bright Value,” which we want to make a reality, as ‘making our information society fairer by securely identifying the risks and opportunities buried in records’ using the data analysis knowhow and highly-advanced AI technologies we have developed,” commented Masahiro Morimoto, founder and CEO of FRONTEO (TSE: 2158).

FRONTEO (TSE: 2158) who is Asia’s leading legaltech innovator powered by AI and expanding its AI solution “KIBIT” into healthcare and business intelligence as a SaaS (Software-as-a-Service) recurring revenue model for non-legal clients. Guided by the mission to illuminate the darkness lurking in data by securely identifying the risks and opportunities buried in records by utilizing technology, FRONTEO (formerly called UBIC) was founded in Aug 2003 by Masahiro Morimoto as a legaltech company supporting eDiscovery (electronic evidence disclosure) and digital forensic services for clients involved in US and international cross-border litigation, corporate investigations and intellectual property disputes. The data analytics platform Lit i View with “predictive coding” technology which supports multiple Asian languages (China, Japan, Korea) was developed in 2012 and was further enhanced with the AI engine KIBIT developed in Nov 2015 that is leveraged upon to develop the AI Solution business for non-legal clients. FRONTEO’s KIBIT series had acquired the number one market share of 26.8% based on sales value in the domestic natural language analysis market for 2016 and 2017 in the independent ITR survey announced on 11 Dec 2018, which is nearly doubled that of the 13.9% share held by the second place vendor. KIBIT uses the proprietary and unique “landscaping” AI technology to learn the “tacit knowledge” (experience and intuition) of human experts and, unlike all other AI technologies, KIBIT requires only small volume of data for effective machine learning to produce good quality output and solve customers’ problems.

FRONTEO’s business model is a mix of project-based revenue (legaltech business) and recurring revenue (AI Solution business) with improving profitability in overall TTM (trailing twelve months) operating margin of 8.9%, ROE (= EBIT/ Equity) of 22% and ROA of 7.6%. The AI Solution business turned profitable in 3Q FY18/03 after hitting an inflection point in moving from PoC (proof-of-concept) for its clients to the full-launch stage and has amassed a wealth of solutions and cases to aid marketing; sales jumped 1.4-fold yoy and clients grown 1.8 times yoy to more than 121 customers as at 2Q FY2019 (Sept 2018). FRONTEO’s AI Solution business serves clients in the financial & healthcare industry/ “KIBIT Knowledge Probe” (MUFG Bank, Yokohama Bank, Resona Bank, Aeon Bank, SMBC Nikko Securities, Mitsubishi UFJ Morgan Stanley Securities; Daichi-Sankyo, LITALICO), compliance/ ”KIBIT Email Auditor” (Toyo Tires, Innolux, Evergreen Marine), and patent analysis/ ”KIBIT Patent Explorer” (Denso, Kikkoman, Sapporo, Kuraray, Showa Denko, Toray, Toyobo). FRONTEO launched its second AI engine Concept Encoder in Dec 2018 for the healthcare industry in drug discovery and clinical trials. Whereas KIBIT excels in natural language processing, Concept Encoder can analyze data other than language, including symbols and gene expression. The AI Solution business is expected to contribute 13% and 7.1% of sales and operating profit respectively in FY2019/03. In its new medium-term plan announced in May 2018, FRONTEO expects its AI Solution business to increase in sales from 1.8bn yen in FY2019/03 to 5.8bn in FY2020 and 11.8bn yen in FY2021, and contribute 31.2% of operating profit in FY2020 (645m yen) and 57.1% in FY2021 (2.418bn yen).

In its legaltech business, FRONTEO has far superior eDiscovery support tools in which Lit i View is the only platform that supports Asian languages without the garbling problem and the only one that offers end-to-end eDiscovery services that combines a workflow system plus AI analytical tools KIBIT that increases the efficiency and accuracy of the document review process, a critical aspect of eDiscovery that accounts for 70% of the cost. Lit i View platform has a review management dashboard where clients can have up-to-the-minute metrics on review progress, which includes a heat map within Lit i View that provides a detailed snapshot of reviewer progress and productivity and enables course corrections as needed. Most litigation cases in the US do not reach trial (examination of facts in a public court). Usually, a settlement is reached during pre-trial. However, unlike in Japan, in the US the victor of a settlement is largely determined by the discovery process, wherein evidence is presented to each side. Therefore, discovery plays a key role in ensuring that the terms of a settlement are as favorable as possible. As such, discovery can determine the outcome of litigation and the discovery process account for 70% of the cost of litigation.

However, despite its overwhelming technological superiority, FRONTEO has faced great difficulties over the years in trying to break through the established practices of US litigation cases that involve Asian companies, its main market, and grow its market share from the current 3%, as well as achieve a stable targeted operating profit margin of 10%. eDiscovery providers are often selected by the Asian companies’ US subsidiaries or by US attorneys, not by Asian companies themselves. In other words, when a lawsuit is filed in the US, Asian companies have a strong tendency to leave the selection of lawyers and other service providers to their local subsidiary. US lawyers tend to leave the choice of eDiscovery providers to their litigation support teams but the attorneys have a powerful sway in the vendor decision. Thus, unlike the other AI innovators we have investigated whose solutions were readily and rapidly adopted by their clients to solve high-value problems, FRONTEO was an odd case that stood out because the legal industry was particularly resistant to utilizing AI despite its effectiveness since the hours spent can be billed back to the clients and the attorneys make or influence the decisions on the IT vendor based on “relationships”. In short, when FRONTEO targeted its powerful AI legaltech solution to the end corporate clients in Asia involved in litigation suits and to the US litigation support team, it neglected its ultimate client – the US attorneys – and lost the war.

A positive inflection point in its legaltech business could be near after the completion of structural business reforms at its US subsidiaries in FY18 helped FRONTEO to win several large Asian (including Japanese) clients in 1H FY2019 and the management comments that “We are finally able to do what we’ve been really wanting to do” and expects a strong 2H pipeline with several more orders. After 15 years since its founding in 2003, FRONTEO finally established a global legal headquarters in US in April 2018 with global offices under direct control of this HQ to strengthen the overall sales structure and better build relationships with US law offices, strengthened internal controls, and undertook actions to curtail unprofitable projects in the US.

On 14 Nov 2018, FRONTEO announced its 2Q18/Sep results (Apr – Sep 2018) in which 1H sales declined 4.1% to 5.61bn yen and operating profit jumped from losses to 196m yen. Revenue fell due to cutbacks on unprofitable projects and restructuring. Balance sheet is relatively healthy with debt of 2.86bn yen (gross cash 4.11bn yen, gross debt 6.98bn yen), or 9.3% of market value. In its new medium-term plan announced in May 2018, FRONTEO estimates FY2020/03 sales of 20bn yen (legaltech 14.2bn yen, AI 5.8bn yen) and operating profit of 2.065bn yen (legal tech 1.42bn yen, AI 645m yen); FY2021/03 sales of 30bn yen (legaltech 18.2bn yen, AI 11.8bn yen) and operating profit of 4.238bn yen (legal tech 1.82bn yen, AI 2.418bn yen).

On FRONTEO’s proprietary AI engine KIBIT which utilizes the “landscaping” machine learning technology, CEO Morimoto comments: “FRONTEO has developed our AI engine KIBIT through our services for the uncompromising task of finding evidence in cross-border litigation. This requires us to find data that can be used as evidence from a huge volume of text data within limited time. To meet this challenge, KIBIT learns tacit knowledge obtained by attorneys through experience or intuition and extracts relevant data from a vast amount of text data in accordance with the judgment criteria of attorneys. However, the data from which KIBIT can learn the judgment criteria of attorneys is not always available in large quantities. What matters then is whether the AI engine can learn from a smaller volume of data. Essentially, texts are ambiguous enough to allow a variety of interpretations, and it is indeed difficult to extract required data from them. In the face of such restraints, FRONTEO has developed a proprietary machine learning technology of ‘landscaping,’ or an algorithm to process natural language, which deftly identifies the specific features of a small volume of data and makes judgement that can be consistently applicable to a larger volume of unknown data, functions in a manner akin to landscaping, or visualizing a complete scene from a narrow field of view. This ability makes it possible to streamline such operations as checking documents of massive volume, which requires judgement of humans, to significantly reduce operational burdens. Our AI software has proved to be more than 90% accurate in extracting information for e-discovery reviews and avoids the wide discrepancy in review results that often result from human error. relevant legal documents will no longer be omitted as often happens when only keyword searches are conducted and keyword settings are misconfigured. Although in litigation, e-discovery is the most expensive process, costs can be cut drastically with our AI.”

“FRONTEO’s KIBIT series had acquired the number one market share of 26.8% based on sales value in the domestic natural language analysis market for 2016 and 2017 in the independent ITR survey announced on 11 Dec 2018, which is nearly doubled that of the 13.9% share held by the second place vendor. According to the ITR survey, the total sales figures for 2017 in the five main markets of AI (image recognition; speech recognition; speech synthesis; language analysis; and search) were 11.6 billion yen, showing a rapid increase of 65.2% from the previous year. Among the five major markets, image recognition and language analysis are cited as two markets where market size is large and expectation for future growth can be expected.  The introduction of language analysis has focused on utilization at the current call center which is progressing, but it is expected that introduction will spread to a wide variety of fields in the future. The e-discovery support business that FRONTEO has been working on since its establishment in 2003 is equipped with the language analysis technology KIBIT series that was developed independently for digital forensics and used in the Legaltech business from 2012, We are developing AI solution business for outside customer companies from the year 2014. FRONTEO was able to acquire and maintain the position of a leading domestic AI language analysis company serving customers in a wide range of industries including manufacturing industries and financial institutions and used in various business scenes such as customer support, technology development, product development and marketing. At present, KIBIT is in operation not only in Japan but also in the U.S., South Korea and Taiwan, among other countries and territories. Furthermore, KIBIT is expanding into other domains of application beyond the initial purpose of finding evidence in cross-border litigation. KIBIT also has the advantage of being utilized at relatively low costs, as it is offered in a SaaS (Software-as-a-Service) application format. We have expanded the number of companies introducing applications from international litigation support to data analysis in general corporations exceeding 100 companies as at June 2018, a yoy growth by 1.5-fold.”

When asked about the origin and meaning of the word KIBIT and how the “landscaping” AI technology works, CEO Morimoto explains: “Learning ‘tacit knowledge’ is a special feature of KIBIT. The name KIBIT is derived from the Japanese word ‘kibi’ (meaning mind of the heart) and “bit,” the smallest unit of information in computing. KIBIT thus incorporates our desire to develop AI that can understand the subtle elements of human thought. KIBIT is well fitted for text analysis. It features AI-related technologies that perform learning and assessment processes and know-how that has been accumulated and systematized through on-site experiences of data analysis. Built on these strengths, KIBIT can learn, from a small volume of training data, the human subtleties of persons who selected the data or the tacit knowledge grounded in such persons’ experiences and judgment.”

“Here is a brief explanation of the ‘landscaping’ technology. When analyzing text data, KIBIT identifies the parses (word classes) and extracts certain words to calculate the degree of importance for each extracted word in relation to the targeted information. In calculating the degree of importance, KIBIT uses the concept of transinformation to determine whether the word is relevant. Next, KIBIT compiles the degree of importance for each word within the text to assign a score, realigning data by score in a descending order. These processes are performed in ‘landscaping’, an algorithm independently developed by FRONTEO as a method of learning and inference for KIBIT. ‘Weight Refinement’ is a special function and unique algorithm of KIBIT that optimizes the degree of importance attributed to words. Weight Refinement makes it possible for KIBIT to identify data characteristics that cannot be found through the calculation of transinformation alone. As its feature, the algorithm allows KIBIT to perform fully with a small volume of data and learn without building a large-scale server environment. This algorithm allows KIBIT to learn the tacit knowledge of experts – or knowledge based on the experiences and judgment of humans.”

“At FRONTEO, we do not consider big data to be merely an accumulation of data, but a collection of people’s thoughts and behavior outcomes. We define behavioral informatics as an analytical interpretation of behavior, and the synthesis of information science (including statistics, mathematics, data mining, and pattern recognition) and behavioral science (including psychology, criminology, and sociology). Conventional approaches to big data merely analyze past incidents, from which they extract some facts. But, in behavioral informatics, we are able to predict the future, and we do so by basing our analytics on human cognition and by generating patterns of human and social behavior.”

CEO Morimoto went on to elaborate on the applications of KIBIT in financial institutions, its development to process and analyze beyond natural language text data to images and voices, and the launch of the second-generation KIBIT G2 in Nov 2018: “Let’s take financial institutions, for example. When these entities sell financial instruments, various laws and regulations must be abided by, including the Financial Instruments and Exchange Act, voluntary regulations of the Japan Securities Dealers Association and the Insurance Business Act. Financial institutions also must check several items, such as the appropriateness of transactions in proportion to customers’ willingness to purchase, knowledge, investment experience, allocation ratios and other factors, inadequacies in the documents offered to customers, consent by customers’ family members, and any unreasonable aspects found in customers in their discussions. However, human eyes cannot check all cases, and judgment criteria may differ among persons in charge according to their skills and experiences. Moreover, the quality of checks may not be secured because of possible human errors due to fatigue, among other reasons. Here is a case in which KIBIT is used for a financial institution. The Financial Instruments and Exchange Act prohibits financial institutions from conducting inappropriate solicitation and calls for the necessity of protecting investors. Financial institutions must see to it that their salespersons do not churn, or make their customers frequently buy and sell securities, rather than recommending financial instruments that matches the knowledge, experience, assets and investment purposes of customers. In an application example of KIBIT, it can be inferred that, based on the age, investment ratio, motive and other factors, the investor does not have ample reason to change the currently held financial instruments to something else. KIBIT, as an AI engine, learns such tacit knowledge, makes judgment similar or close to human judgment at a high speed, and finds similar records from among a massive volume of records.”

“At FRONTEO, we believe that the progress in AI is largely divided into two stages. The first is the stage in which AI and data will be increasingly used within existing organizations to drastically improve productivity. For example, AI would more efficiently analyze customers’ voices at call centers, and AI for conducting production management would be introduced at plants to enable on-demand production. The next is the stage in which AI machines will coordinate with each other beyond the boundaries of existing organizations, promoting use of data on an even wider scope. For example, AI at a call center determining that a certain new product is provoking many complaint calls would coordinate with the AI system in charge of production management at the related plant to temporarily reduce the production volume of the product. Moreover, it is expected that such coordination between AI machines will be conducted not only among existing organizations of an industry but beyond the boundaries of industries to create complicated ecosystems. Over the course of this process, it will become popular for AI to analyze multiple modalities including language, figures and images in an integrated manner. Research has been under way to equip FRONTEO with multiple modalities, a mechanism that allows simultaneous processing of different types of data like texts, images and voices, to make it possible to analyze data other than language. Moreover, FRONTEO is working on the idea of creating an autonomous AI platform, in which multiple AI machines communicate with each other in an autonomous and distributed manner to process data so that the scope of analysis expands automatically at a high speed. The future KIBIT platform will serve as the integrated system supporting these complicated structures and autonomously processing big data to generate high-level, integrated results.”

“On 5 Nov 2018, FRONTEO began offering our second-generation AI engine KIBIT G2. Two functions have been added to KIBIT G2. The first is API ‘KIBIT-Connect’ that enables cooperation with other systems. It is aimed at cooperating with business systems etc of the company, and it is published for a fee. We developed it as a REST API that can be called with HTTP so that it can easily cooperate with the system on the cloud. By using KIBIT-Connect, KIBIT G2 can acquire various data from systems such as relational database management system (RDBMS) in the enterprise, ERP, CRM and so on, and return analysis result to business system , It became easier to use in business. FRONTEO will also start providing OEM for KIBIT G2 engine. Companies that receive OEM will be able to create software with AI function by incorporating KIBIT G2 engine into proprietary software. The second new function is parallel processing using multiple servers. which shortens the analysis time. In KIBIT G2, customization of analysis algorithms also became possible depending on customers’ uses, which became applicable to a wider range of applications than before.”

CEO Morimoto shared several new developments in KIBIT Patent Explorer 19 and KIBIT Find Answer: “Our patent search and analysis system ‘Patent Explorer 19’ was selected as a finalist (top six) in the Product Innovation Competition at the world’s largest legaltech exhibition ‘Legaltech New York 2019’ to be held from 28-31 Jan 2019. Launched on 5 Nov 2018, ‘Patent Explorer 19’ smooths patents research essential for product development and patent application. By simply giving small amount of patent document information as teacher data to the AI engine KIBIT, existing patents in the patent database can be automatically converted into scores and displayed in descending order of similarity, substituting the judgment made by a person in extracting similar patents and speeding the patent search. The number of companies adopting Patent Explorer 19 has progressed in a wide range of industries from chemistry, materials, machinery to F&B manufacturers and has increased 2.5-fold yoy as at Nov 2018 to exceed 50 In response to the growing demand for patent analysis efficiency improvement. This product was developed jointly with Toyota Technical Development and launched in October 2015. In March 2019, we plan to offer ‘Email Auditor 19’ with a new engine, business data analysis support system ‘Knowledge Probe 19’, and Q&A system ‘Find Answer 19’.”

“On 30 July 2018, we launched our AI FAQ system ‘KIBIT Find Answer’. In general search engines, we will narrow down the answers by putting keywords one after another in order to reach the answer you want, but as you do so, the answer itself will not come up. Also, some skill is required on the search side on what to set as a keyword. However, in the case of KIBIT Find Answer, you do not have to worry about what to set as keywords. It’s okay to just insert texts as you thought, just like asking people a question by email or chat. No matter how long the text of the question is, KIBIT will capture the characteristics of that sentence, absorb the fluctuation of expression and pick up the nearby questions of the past. The more you enter a question sentence, the more KIBIT learns its characteristics. It is opposite to the world which narrows down by putting in keywords. It is a system that can be utilized for customers’ inquiries and as an internal knowledge-sharing mechanism in departments where highly specialized questions are gathered, such as IT helpdesk, legal department, personnel affairs and general affairs. Up until now, it was necessary to prepare and teach contents that KIBIT learned beforehand, but if Find Answer is put in as words are spoken to it, KIBIT immediately reacts. We are able to create highly interactive technology to pull related data. We think we have expanded the world that can use KIBIT more interactively and conscious of human natural language, that we can be cared for. For example, this can be used in a place where interactive communication such as customer support with a robot occurs.”

CEO Morimoto also shares his excitement about the potential of FRONTEO’s second AI engine Concept Encoder: “In addition to text data, we aim to promote the use of medical big data with our new AI solution which analyzes numerical data. Our wholly-owned subsidiary FRONTEO Healthcare has developed a new AI ‘Concept Encoder’ for healthcare, acquired patents in Japan, and started full-scale offering. It will become the second major AI business in the Group in addition to KIBIT. Despite being an enormous amount of precious information sources, text data such as electronic medical records among medical big data had been limited in scope of use so far. These are due to the fact that descriptive formats and descriptions are quite diverse and concrete for each facility and individual and it is difficult to handle them as homogeneous data for analysis. Concept Encoder was developed to apply the statistical analysis method that has been utilized for many years in the healthcare field, so that it is possible to analyze text data efficiently, as well as co-analyze with numerical data such as gene expression information. In FRONTEO Healthcare, we will contribute to the development of healthcare industry by objectively evaluating every data by exploiting the Concept Encoder, clearly indicating the analysis process, and realizing the provision of a service that our customers continues the use with peace of mind. In the field of healthcare, we utilize the tacit knowledge of doctors and nurses to predict the changes in the patient’s condition by analyzing the information on electronic medical charts. In the field of business intelligence, projects are progressing to improve customer satisfaction and employee satisfaction by tacit knowing the opinions of salespeople and customers. And in the field of digital marketing, we analyze customer’s opinions and apply it to product development and corporate strategy by making use of the tacit knowledge of excellent marketers.”

“On 18 Nov 2018, we acquired patent (Patent No. 6346367) for our second AI engine ‘Concept Encoder’, a epoch-making new search technology dedicated to healthcare to speed up discovery of new drug candidate compounds. Utilizing a different approach from conventional search or simulation technologies, a major feature of this new search technology is that researchers engaged in the development of novel drugs at drug manufacturers can now use natural language processing technology to search for and investigate the relationship between their hypothesis and the contents of the literature in the public database information. Researchers can find relationships with diseases that are likely to be related to their own new hypothesis and drugs that change similar genes and it will be easy to reach concrete target candidates for new drugs. Specifically, after letting Concept Encoder learn the public database information and the text information of the thesis (literature), when creating hypotheses of the researcher in natural sentences and inputting it to the Concept Encoder, the hypothesis target related gene network etc. based on the relevance strength and is visualized with a score (numerical value). It can also emerge new diseases that are closely related to specific compounds, and it is possible to obtain a wide range of outputs that are not possible with conventional database searches. Furthermore, since vector operation is carried out, it is possible to freely remove elements unnecessary for searching, such as specific diseases and target gene networks related to existing drugs, and analyze only differences. We developed and aimed to effectively analyze and utilize healthcare related big data including massive amounts of free text data based on evidence (evidence). We introduce and realize statistical methods such as significant difference test essential to ‘Evidence based medical (EBM)’. This function is one of the big strengths of Concept Encoder, which has never been before, which will speed up the discovery of new drug candidate compounds.”

“In the R&D department of pharmaceutical companies, updating information on a daily basis by checking the research paper information and the public database is an essential task for quickly finding new drug candidates. Meanwhile, the fact that the time and effort of researchers are greatly spent to keep track of trends in pharmaceutical research both in Japan and abroad in a timely manner is also a big challenge. There are numerous information disclosure databases of genes, proteins, compounds, etc. that support the base of drug development worldwide. In order to make the work of the researcher more efficient, it is necessary to create a database from innovative methods called in-vitro analysis such as animal experiments and cell culture experiments. It is important to be able to substitute virtual means such as in-silico analysis or to be able to pinpoint target information from public information.”

“The analysis also features ‘light processing’ that eliminates the need for large expensive equipment such as supercomputers and large-scale server groups. Methods for simulating the action of drug candidate compounds using AI with public database information have been actively conducted and several domestic companies have already achieved R&D efficiency.”
“This technology is a practical and convenient technology that can be used not only for drug candidate search but also for analyzing various networks in the future. Concept Encoder is also capable of co-analyzing with data other than text, and we are conducting co-analysis with numerical data such as gene expression information, vital and various examination values accumulated in the health care area.”

While FRONTEO is now profitable and more stable, CEO Morimoto shared that his personal and entrepreneurial journey to start FRONTEO has been full of struggles. CEO Morimoto shared reflectively the inspiring story, including the three stages of FRONTEO’s growth: “I was born in Toyonaka city, Osaka prefecture. I longed to be an astronaut when I was a child and I studied how to do to become an astronaut. Then, I wanted to be a pilot of a fighter aircraft. After graduating from high school, I advanced to the Defense Academy. Unfortunately my eyes got worse when I went to the Defense Academy and I gave up the pilot’s way and became a maritime self-defense officer. I joined Applied Materials Japan in 1995 when I was 29. At first I had no intention of becoming an entrepreneur. But I saw how Japan, one of the world’s leading patent holders, struggle with international lawsuits. I developed a strong sense that I had to do something for those Japanese companies that were incurring huge financial losses as a result of litigation abroad. At that time, there were not many forensic or e-discovery services in Japan that offered strong support.”

“That was why, after having accumulated from scratch the know-how required to set up a company, I established my own enterprise at the age of 37. When I founded FRONTEO in 2003, it was sailing as a single person, but gradually my friends increased, and we listed the company on both Tokyo Stock Exchange and NASDAQ. But growth does not stop. My mission today is to support companies worldwide with our AI, which can emulate experts’ behavior and apply their wisdom to that we can continue to come up with appropriate business solutions. Those who want to set up their own company must have a clear mission, and to commit to this with persistence and the support of a strong team.”

“Our original symbol is the sun, meaning to illuminate the darkness lurking in the data of all over the world. We do not miss risks and opportunities buried in records by utilizing state-of-the-art AI technologies that we have cultivated and provide optimal solutions. Various axes spreading radially show the spread and possibilities of businesses centered on artificial intelligence. We want to bring about the realization of bright value and a fairer world in the information society. FRONTEO is a combination of the words ‘Front’ which means cutting edge and ‘eo’ which is to move forward, a Frontier Technology Organization. At the time, FRONTEO did not have proprietary technology or engineers, so we imported tools from the US. Our profile rose due to eDiscovery awareness campaigns in the domestic market. In addition, in December 2006, revised Federal Rules of Civil Procedure (FRCP) mandated the disclosure of electronic data evidence in US court cases, boosting demand for our services.”

“Stage 1 (FY03/10 – Q3 FY03/11) of our growth is starting our in-house development of Lit i View specialized in Asian languages. We found it difficult to adapt US-oriented products to the Japanese market merely by asking US companies to tweak their products. As such, in FY03/10, we decided to change direction and allocate management resources, primarily personnel, to move development in-house. In September 2009, we started development of Lit i View, an AI-powered platform to improve the speed and accuracy of eDiscovery and covering all eDiscovery processes. We completed Lit i View version 1.0 in March 2010. From the start, Lit i View consolidated all discovery processes on a single platform for increased efficiency in the document review process and offered compatibility with East Asian languages. Steps required in the review process in eDiscovery are data identification, preservation, and collection, then processing and analysis to identify and exclude unnecessary data. All processes of eDiscovery are connected and at times require going back to previous processes. Lit I View can carry out all processes on a single platform; structures workflows to streamline reviews; quickly reflects feedback from users on the ground as it was developed in-house; and supports East Asian languages.”

“Stage 2 (Q3 FY03/11 – FY03/16) of our growth is establishing our AI-embedded Lit i View and NASDAQ listing. In FY03/10, a decline in orders following the global financial crisis and increased personnel expenses led to an operating loss. However, in FY03/11, FRONTEO posted a substantial increase in operating profit. This was because the successful development of Lit i View enabled the company to win large accounts, including document review projects and increased productivity of the review process in which we helped reduce the hours required to one-tenth. We positioned FY03/12 as a make-or-break period for our second phase, and conducted upfront spending on personnel, hardware, and software; we increased headcount to cultivate the US market, constructed a data center, and incorporated predictive coding that leverages AI research into Lit i View.”

“Predictive coding was developed in response to demand for streamlining the review process, the core and costliest element of eDiscovery. We set up a development team in Q1 FY03/12 and started research in Q2. In March 2012, we completed development of Lit i View version 4, the first version using AI. This was an industry-leading predictive coding software using our proprietary AI ‘landscaping’ technology to enable the automatic and highly accurate extraction of Japanese text likely to be included as evidence for disclosure in the review process. Increased sorting efficiency ensured the speedy and accurate compilation of evidence that lawyers required. The second-generation AI-powered Lit i View version 6, developed in January 2013, featured increased accuracy and speed of extracting litigation documents. In March 2013 we completed Lit i View version 6.5, which also supported Chinese and Korean, and subsequently upgraded our AI software and continued to add core features. In response to customer needs, we have developed AI engine KIBIT that can predict human behavior, the base of the current AI Solution business. KIBIT searches at over four thousand times the speed of a human auditor. A human reviewer can on average search 80 documents an hour. Our predictive coding program can review over 300,000 documents an hour and with 30% greater accuracy than a human reviewer. Our predictive coding system is the only one in the world specifically designed to accurately search in major Asian languages in addition to English. It has reduced costs by up to 40% when compared with other search systems.”

“Expansion into the US market, a growth driver Lit i View, powered by the company’s AI software, covers all of the eDiscovery processes and streamlines the review process, which accounts for the bulk of costs. Still, our market share has languished in the single digits. This is because eDiscovery service providers are often selected by Japanese companies’ US subsidiaries or the US law firms in charge of litigation, while many of FRONTEO’s customers are Japanese companies. In addition, we lacked a sales organization in the US.”

“In order to break through this impasse, we have undertaken the following initiatives. We listed ADRs on NASDAQ in May 2013 to raise our profile as a US listed company to acquire US companies on better terms and become a client of major US law firms. By becoming a client of major US law firms, we can better understand the thinking of leading attorneys and obtain useful information. We expanded our sales channels through M&As. In August 2014 FRONTEO purchased US eDiscovery consultancy and solutions provider TechLaw Solutions (TLS) which was established in 1983 and was loss-making then. In July 2015, we acquired EvD which was established in 1997. TLS was well-established, offering services related to US litigation and links to the Department of Justice. EvD had the technological capability to provide one-stop eDiscovery services and a track record of serving large corporations and law firms. Through the TLS acquisition, we deepened relationships with law firms on the East Coast of the US, and through EvD, we strengthened ties with firms on the West Coast which is home to many US subsidiaries of Japanese companies.”

“Stage 3 (FY03/16 onward) of our growth is expanding into the US and other AI applications. The two acquisitions of TLS and EvD not only expanded our sales channels, but also enabled it to win large projects and offer comprehensive legal services. However, EvD, which had been unlisted, had to undergo swift and sweeping reforms to internal controls to deal with quarterly disclosure and auditing, which curtailed marketing. In July 2016, we merged and consolidated our three US subsidiaries into two companies, FRONTEO USA and FRONTEO Government Services. In 2017, we replaced management at our principal subsidiary, FRONTEO USA, as part of restructuring.”

“In FY03/18, FRONTEO conducted a sweeping reorganization of the US business, where we eliminated low-profit projects to maximize profit margin and established a unified cross-border sales team to acquire large project wins in Asia by leveraging its proprietary platform Lit i View, which supports multiple East Asian languages, while on the cost front, we managed to reduce costs by scaling back the office responsible for review work, and streamlining the payroll. With the completion of this restructuring program in FY03/18, operating profits at the Legaltech segment demonstrated marked improvement with every quarter. Having now assembled the global infrastructure necessary to secure large contracts in Asia, FRONTEO’s plan for FY03/19 onward is to embark on a phase of aggressive expansion, during which we will see to obtain large projects from Asian clients as well as further strengthening the Lit i View platform.”

On the growing success of FRONTEO’s AI Solution business for non-legal clients, CEO Morimoto shared his thoughts on growing the business further with the KIBIT Partner Network Program (KPN) and the BizDevOps Lab to promote and support the adoption of AI: “We have been expanding the AI technology cultivated for Lit i View to other applications. Lit I View has high recall and precision rates due to our internally developed AI software using the ‘landscaping’ machine learning technology. With limited training data, this technology can acquire tacit knowledge in specialist fields (eDiscovery) and analyze big data. We launched a new software development project in November 2013 utilizing this proprietary AI technology, currently KIBIT, as we aim to evolve from an eDiscovery specialist to a behavioral analytics company. Currently, our AI Solution segment is divided into two areas: business intelligence (BI) and healthcare. Software powered by KIBIT is being developed in a variety of fields. These include the commercialization of email analysis and auditing system KIBIT Email Auditor in April 2014; joint development of patent research and analysis system KIBIT Patent Explorer with Toyota which started in December 2014 and commercialized in October 2015; joint development of a patient fall prediction system in February 2015; and business data analysis support KIBIT Knowledge Probe in October 2015.”

“FRONTEO’s AI Technologies provide solutions in many different fields and have contributed to developing a more enriched society. In litigation, we provide one-stop services ranging from identification, preservation and processing of data, and document review to preparation of data to be submitted, etc. For government offices, we offer support for analysis of fabrication, loss of electronic records and collecting related information. We also provide curriculum on the use, handling, management and reporting related to the latest technologies and relevant data. In medical care and nursing care, we support advanced and high-quality medical diagnosis by analyzing big data, and contribute to solving resource-shortage problems on site. In compliance, we detect potential compliance violations in advance by analyzing daily business reports and discussions with customers. In patents and intellectual property, we provide support for investigating and analyzing advanced technologies and technical trend surveys, etc. In manufacturing, we assist with new product development and service improvements by analyzing customers’ comments collected on a company’s or product’s website; and help manufacturers transfer knowledge, skills and implied knowhow from their experienced technical staff. In finance, we check whether or not applicable laws and regulations are adhered to and all necessary explanations are given when financial products are sold. In business improvement, we contribute to increasing our customers’ level of satisfaction by extracting their complaints and signs of dissatisfaction which staff may not be aware of from discussions with customers.”

“We have introduced KIBIT to more than 120 domestic and overseas companies (cumulative as of the end of September 2018) such as finance, manufacturers, services, transportation and government agencies, and have been widely supporting business efficiency improvement and social productivity improvement. On 22 Nov 2018, FRONTEO announced our KIBIT Partner Network (KPN) program to utilize the customer network of our partner companies to promote awareness of AI solutions centered on KIBIT and promote expansion of customer contacts in potential industries and business types. KPN prepares 3 levels of certification in Gold, Silver and Bronze according to partner’s expertise and collaboration level and also helps train AI engineers based on KIBIT. Our KPN partners include SCSK (TSE: 9719), TIS Inc (TSE: 3626), System Information Co (TSE: 3677), Mitsui Information (MKI).”

“FRONTEO AI BizDevOps Lab, a facility that promotes and supports the adoption of AI, was launched on  16 Nov 2018, to assist customers in overcoming obstacles to AI adoption by creating and optimizing training data and conducting analyses on results derived from AI. The facility provides these services based on successful examples of adoption and accumulated expertise. We will be able to more quickly and effectively make proposals to customers and give feedback to its technological team thanks to the unification of our consulting, analysis, and application development teams.”

While we find FRONTEO’s AI Solution recurring revenue business to be promising, the legaltech project-based business is troubling. CEO Morimoto explains patiently the eDiscovery industry and FRONTEO’s legaltech business: “Most litigation cases in the US do not reach trial (examination of facts in a public court). Usually, a settlement is reached during pre-trial. However, unlike in Japan, in the US the victor of a settlement is largely determined by the discovery process, wherein evidence is presented to each side. Therefore, discovery plays a key role in ensuring that the terms of a settlement are as favorable as possible. As such, discovery can determine the outcome of litigation. Civil cases in the US have applied the discovery process since 1938. This is a system where the plaintiff and the defendant both provide relevant information upon request. In December 2006 revised Federal Rules of Civil Procedure (FRCP) mandated the disclosure of electronically stored information (ESI) as evidence in US court cases. eDiscovery has benefits for both plaintiff and defendant. Information and points subject to dispute are organized, making a settlement easier. Even if the plaintiff is an individual, that individual can take on a major corporation. eDiscovery also enables a verdict based on objective facts and promotes settlements based on the adversarial system (where two parties present their case before an impartial third party), the foundation of the legal system used in the US.”

“Discovery is not used in the same way in Japan or other parts of East Asia, so many Asian companies are unfamiliar with the process. When a lawsuit is filed in the US, Asian companies have a strong tendency to leave the selection of lawyers and other service providers to their local subsidiaries. US lawyers also have a strong tendency to leave the choice of eDiscovery providers to their litigation support teams. As such, Asian companies can be at a disadvantage when validating eDiscovery price estimates or dealing with cost increases that exceed initial estimates. If the eDiscovery provider does not have strong Asian language capabilities, translation costs are also incurred. Furthermore, even for short cases eDiscovery requires at least six months, and can take five years or longer. Ballooning litigation costs may lead companies that lack sufficient financial resources to settle on unfavorable terms in order to finish litigation quickly.”

“Lawyers’ fees comprise around 30% and eDiscovery costs about 70%. The core of eDiscovery is document review and the review process accounts for around 70% of eDiscovery costs. The eDiscovery market has been expanding at an average annual rate of 15% to US$21bn in 2022 according to Transparency Market Research. FRONTEO competes with around 1,000 other companies in the eDiscovery market. However, consolidation is occurring amid fierce competition. Unlike FRONTEO, which develops tools internally, competitors purchase systems to use in eDiscovery processes from the same three or four eDiscovery tool vendors. However, the traditional business model is shifting, as competition intensifies and prices fall while data volumes (thus workload) increase, squeezing margins. Under such an environment, our company group will, as an eDiscovery vendor from Asia, press ahead with expansion of businesses in the eDiscovery market through acceleration of cross-border sales activities on a global scale by capitalizing on Asian-language compatibility, a strength of the independently developed eDiscovery support system, ‘Lit i View’; high efficiency realized under the AI technology, ‘Predictive Coding’; and capabilities for offering one-stop solutions for the entire eDiscovery process, as well as on our expertise based on abundant track records of providing support.”

“eDiscovery has several steps such as identification, preservation, collection, processing, analysis, hosting, document review, and production. We charge for each of the steps. Hosting service is one of the steps of e-discovery, and its purpose is to store the data which has been loaded to the hosting server after collection, processing, analysis, and document review. Unlike the e-discovery process which only takes between one to twelve months to complete, hosting service usually lasts more than five years. One reason that the data which has been processed and reviewed by attorneys must be kept for a long time is that there is high possibility of reusing the data in case of multiple lawsuits and other issues for one particular case, for instance. Furthermore, these data are too valuable and expensive to discard since these data can be leveraged across multiple matters. These are the reasons why hosting revenue has been growing. It is a kind of recurrent revenue for us.”

“FRONTEO’s proprietary platform Lit i View is the only solution that offers companies end-to-end eDiscovery services  that combines a workflow system plus AI analytical tools KIBIT that increases the efficiency and accuracy of the document review process, a critical aspect of eDiscovery that accounts for 70% of the cost. As an example, we have developed a review management dashboard where clients can have up-to-the-minute metrics on review progress, which includes a heat map within Lit i View that provides a detailed snapshot of reviewer progress and productivity and enables course corrections as needed.”

“Conventional eDiscovery tools developed in English-speaking countries cannot accurately process legal documents written in Asian languages or multi-byte characters in Chinese, Japanese or Korean (CJK), without experiencing problems such as garbling. FRONTEO initially focused on e-Discovery for these multi-byte languages. Asian companies, which thus are at a disadvantage in terms of the e-discovery process, have found that our own e-discovery reviewing tool Lit i View that use our proprietary KIBIT AI Predictive Coding provides an effective solution to their problems and improve the quality of reviews, which can account for up to 70% of eDiscovery costs.”

“We help our CJK clients understand how we’re going to organize a complex case that potentially includes multiple languages. We also have forensic collection experts on the ground throughout Asia, which is extremely helpful in targeting and identifying the correct data and collecting it in a way that is forensically sound, which is very important for beginning the eDiscovery process itself. We are receiving very positive reviews from clients in Asian countries, who tell us that they truly need to use Lit i View for documents in Asian languages. The user interface for Lit i View is simple and easy to use and can be customized for some functions depending upon the project needs. This makes adoption of our software solutions relatively easy for U.S. attorneys who appreciate the effectiveness of our software in bridging the language gap.”

“Our strength lies in operations that enable us to integrate and manage data within Japan. This is of particular value to the increasing number of Asian companies that do not want their highly confidential data to leave the country. At the same time, we provide an end-to-end, full e-discovery service, bridging any gap there might be between Asian companies and US attorneys, so that complex matters and projects may proceed smoothly for both sides. One of our customers, which regularly faces cases filed by non-practicing entities (NPEs) in the US, was able to reduce their eDiscovery costs by up to 40% by utilizing our services based on our proprietary AI technology. We have heard that achievement garnered a special company award. In eDiscovery, there has been no significant change in litigation costs or customers’ litigation budgets, yet there has been a steep rise in the volume of data involved (higher customer costs) and greater pressure to remain cost competitive with every passing year FRONTEO aims to take advantage of this situation improving upon Lit I View. We think that our competitors will face difficulty adapting to the changing environment, since their services rely on third-party tools developed by other companies.”

“Today, risk cases such as legal risks such as lawsuits and compliance violations at home and abroad, internal control problems arising through accounting and auditing, cyber security measures such as information leakage from outside invasion, etc. have occurred. In projects where third-party committees are established in recent years, the amount of data to be surveyed and investigated is large and response to report in a short period is required.”

“In response to these circumstances, on 21 Jan 2019, FRONTEO announced our Legaltech Solution Lab which integrates DOC (Discovery Operation Center) and Digital Forensic (Electronic Identification), the two facilities of eDiscovery in International Lawsuit, with FOC (Forensic Operation Center) which conducts fraud investigation. We will utilize practical know-how, such as forensics, discovery, cyber security measures, third party committee surveys, etc., to conduct large-scale data surveys and prompt response to risk deals with our proprietary AI engine KIBIT and the Lit I View series and the research capabilities we have cultivated over many years. We will make maximum use of our know-how in legal affairs and internal control and provide early detection and resolution of problems to a wide range of companies.”

“In addition to increasing the scale of data and shortening the response time, Legaltech Solution Lab also responds to changes in the information recording environment, survey method, fraudulent means and signature of information surrounding companies as follows: “(1) In discovery, records that were once in servers and PCs are also stored in the cloud and mobile terminals, so the importance of cutting-edge digital forensic research techniques such as combining data analysis and log behavior analysis is increased; (2) For forensic, investigation by third party committee requires large-scale data analysis in a short period of time, introduction of latest research techniques such as AI cultivated through discovery and process management are essential; (3) The number of third-party committees established in listed companies increased significantly from 39 in 2017 to 71 in 2018. The accounting and finance problems, such as accounting and asset diversion, account for the most problems, and the number of projects which need extensive investigation by organizational hiding and tampering is increasing; (4) When cybersecurity incidents occur, movement to prevent damage confirmation and secondary expansion, such as identifying spill data and intrusion routes, and taking the next measures urgently is required.”

On the problems faced by FRONTEO’s legaltech business and how they are solving them, CEO Morimoto said: “When a lawsuit is filed in the US, Asian companies have a strong tendency to leave the selection of lawyers and other service providers to their local subsidiary. US lawyers tend to leave the choice of eDiscovery providers to their litigation support teams. We aim to strengthen relationships directly with lawyers rather than through litigation support teams to help it win new contracts. This is because lawyers tend to be more loyal to contract partners and lawyers themselves are salespeople who will be dismissed by their firm if they do not win clients.”

“In the past, the company has laid foundations for future development by establishing a US subsidiary (2007), listing itself on the NASDAQ (2013), acquiring US eDiscovery providers (2014, 2015) and improving our visibility and law office network in the US (through M&A). However, we have yet to fully develop a sales structure for winning large projects in Asia leveraging the use of Lit I View. To pursue our original goal of winning large projects in the US, Japan and Asia, we established a global legal headquarters in the US in April 2018, putting the president of its US subsidiary in charge and placing global offices (in the US, Japan, South Korea and Taiwan) under direct control of this HQ. Under the direction of our global legal HQ, we have integrated our Asian and US sales operations and are working to build and strengthen relationships through initiative such as roadshows that visit US law offices and local subsidiaries in Japan and the rest of Asia.”

“These roadshows serve to show how Lit i View can help make the eDiscovery business more efficient and to secure information concerning litigation support projects for Asian companies at an early stage and contracts for the eDiscovery business. The company has constructed networks with legal representatives from law offices and Asian companies and has built strong ties with attorneys in charge of litigation at major law offices. These achievements are an accumulation of pipelines toward large projects in Asia. FRONTEO is holding many pipelines (not orders, but projects the company has higher possibility of securing than before) for 2H, including major Japanese manufacturers, Asian energy companies, several large US financial institutions, and major US IT companies. These projects are reliable and each is worth almost USD1mn in scale. We are finally able to do what we’ve been really wanting to do.”

COO Naritomo Ikeue also added his views on the legaltech business: “Our Legaltech business started from our passion to want to protect Asian companies from any disadvantage in legal proceedings in the U.S. FRONTEO’s strength lies in its Asian-language compatibility and AI technology, which are incomparable to other companies. eDiscovery (electronic evidence disclosure) is a unique procedure in the U.S. legal system in which both the plaintiff and the defendant disclose evidence to the other party. When an Asian company operating globally is sued in the U.S. or is subject to an investigation by the DOJ, it must disclose evidence in accordance with the legal procedures in the U.S. The discovery process is said to account for 70% of the cost of litigation.”

“At the time when Mr. Morimoto, our President, founded FRONTEO, however, there was no discovery support provider like us in Asia. Therefore, many Asian companies engaged U.S. counterparts for their discovery and suffered many disadvantages such as sending their critical business data to the U.S. without taking any confidentiality measures or bearing translation costs due to Asian-language incompatibility of the software U.S. providers use. In order to protect Asian companies from these disadvantages, FRONTEO has been developing and improving local discovery services (eDiscovery support work in the home country), Asian-language compatibility technology and AI technology to efficiently identify evidence.”

“Current trend where eDiscovery data continues to increase year after year is favorable for FRONTEO, whose strength is AI technology. Volume of eDiscovery data is said to be expanding by 200% to 300% a year because of IT development. This situation is extremely favorable for FRONTEO because our strength is AI technology which reduces the cost to one-tenth compared to eDiscovery by other companies. We can offer our solutions which are far more efficient and have a higher cost-performance ratio to our customers compared to other companies which use more manpower to process the ever-increasing data.”

“We have just completed the structural reform of our U.S. organization and are now moving to a new phase to expand the business. As we started the discovery service, we found for the first time that many Asian companies, which were involved in litigation in the U.S., relied heavily on U.S. law firms, which chose discovery support providers. Therefore, in order for us to expand market share, our sales efforts to the legal departments in their Asian headquarters had only limited effects. Then, as we needed to build our FRONTEO brand in the U.S., we promoted the establishment of our U.S. subsidiary, listing on the Nasdaq and M&A with three U.S. companies. During the fiscal year ended March 31, 2018, we worked on reviewing the cost structure of our integrated U.S. subsidiaries as part of the organizational reform, setting out to integrate and abolish operational bases and create a cross-border sales as our top priority. This significantly contributed to making our organization more profitable and establishing the cross-border sales scheme, which is essential for our Legaltech business to expand in the future. These cross-border sales efforts have already started to demonstrate positive outcomes in winning large projects from companies in Asia.”

“After successfully completing the operational reform during the fiscal year ended March 31, 2018, FRONTEO is now able to start its global sales development aggressively. In addition to the current AI we use in our Legaltech business, we will also bring a revolution in the Legaltech industry by enhancing our AI solutions. As for Lit i View, which is the service platform supporting our litigation support service since 2010, we are currently developing the next generation to speed up scalability improvements and to increase flexibility in the user experience of our software while maintaining its all-in-one feature advantage, which is incomparable to other vendors’ technology. We are aiming to acquire an overwhelming share in the global market with our unique AI solutions that other competitors cannot offer.”

CTO Takeda Hideki also shared how he was attracted to join FRONTEO because of the philosophy and mission of FRONTEO to bring about the realization of fairness and to protect companies in lawsuits, as well as his views on the legaltech business, including a new pricing model to charge by the documents reviewed instead of by the hours so as to better estimate the cost beforehand which is more desirable and fairer for the end client: “I joined FRONTEO in 2009 to lead the R&D of AI technology and FRONTEO introduced to the world the first AI forensic tool in automatic email auditing using machine learning. The philosophy of the foundation of FRONTEO lies in the realization of fairness that Japanese companies want by eliminating the disparity with foreign companies when they fight in international lawsuits. And to realize that idea, the software and data analysis platform Lit i View was born in 2010. Unstructured data generated in business activities such as e-mails and business documents rapidly increased, and as it became big data, it was stacked up to find necessary information out of too much data. It’s like searching for only one particular needle from the mountains of hay. Lit i View” was developed to quickly and accurately discover evidence and fraud information from large amounts of data in international lawsuits. In order to further evolve this and extract information more quickly and with high accuracy, we developed FRONTEO’s proprietary automatic document analysis technology ‘Predictive Coding’ that applied natural language processing, text mining, machine learning and other techniques.”

“FRONTEO further developed Predictive Coding into the artificial intelligence engine KIBIT which analyzes not only conventional clustering and trend analysis but also the qualitative approach based on the outcome of the case database and behavioral science, using the tacit knowledge of human beings, making it possible to predict human behavior and community visualization. Lit i View is trying to further evolve as a platform providing artificial intelligence KIBIT as a core technology that leads the version upgrade of FRONTEO’s existing business in e-discovery, forensics, e-mail audit and related products. Furthermore, it is also being applied to new fields such as intellectual property, medical care, and marketing. We can create technologies with our own hands that make society better and feel the responsiveness of the contribution to society and customers, and the challenge as a business at the same time.”

“There are several types of legaltech business markets, but the big one is an area related to international lawsuits centered on the United States of e discovery, which is growing at 15% per year. Texts written in these natural sentences are mostly analyzed in the business of searching for evidence from internal corporate documents such as communication data, reports, technical documents etc. in the company. Not only the data on the Web but also such in-house data is progressing in volume to become big data, and the fact that the amount of data handled when looking for evidence is increasing is a major factor in market expansion. On the other hand, the pressure to lower the unit price within the market is increasing in recent years. Service vendors offering e-discovery outsourcing services will be forced to face a tough battle in the future, and it is expected that the consolidation of US service vendors seen in recent years will continue.”

“On the other hand, technology vendors that provide software to the industry never deliver products directly to end users; basically they will deliver that technology to the market through service vendors. As the consolidation and reorganization of service vendors progresses, eventually it will become a market situation that a few service vendors intensively attends to the end clients. Therefore, this means that the gap in technologies and services as separate entities is expected to diminish. Looking at the trends of technology vendors in the legaltech industry in the past 10 years, even though vendors whose company size have grown to a reasonable scale and are acquired by major IT companies, the new developments are stagnant after acquisition and they disappear as players This situation is continuously seen. It is a reality that people exit to obtain benefits, and as a result, the impact of growing companies and their technologies does not necessarily correlate in a good way.”

When considering the trend of e-discovery market like this, the situation where FRONTEO is located is unique. First of all, FRONTEO has two faces as a legaltech player, both as a service vendor and also a technology vendor. In cross-border deals that FRONTEO is proud of as a service vendor, FRONTEO is more advantageous than other service vendors who can only respond within the United States because FRONTEO is a company originating in Japan and Asia, while most e-discovery service vendors are US companies. Regarding FRONTEO as a technology vendor, in addition to the strength of being able to process languages ​​other than English correctly and with the natural language analysis AI engine KIBIT as the core, FRONTEO has focused on areas other than e-discovery of evidence in litigation, analyzing analyze various kinds of text data such as patent information analysis. As a result, there is a progress in our general-purpose know-how and analysis engine for text analysis. Having the ability to respond to such diverse analysis is not seen at other e-Discovery technology vendors and we return the know-how accumulated in other areas to the e-discovery area. In addition, Lit I View, our service platform from 2010 which has supported the FRONTEO litigation support service, has been improving scalability and maintaining all-in-one goodness not seen by other technology vendors.”

“In advancing the development of the second-generation Lit i View and AI Review software, it is extremely important that we have the face of both service vendors and technology vendors. Between 2014 and 2016, FRONTEO has acquired three US service vendors. American staff who are experts in the e-discovery business in the United States, staff of cross-border experts in Asia, and staff in the technology department are mixed together, and we are in a hurry to develop new platforms. What we would like to realize with the new AI Review software is the transformation of the business model in the document review of the United States. It is usual to charge the time spent by the reviewer to find the evidence as a human monthly fee when reviewing documents for searching evidence in the world of litigation support.”

“Why is the person’s monthly charge charged? In order to understand it, it is necessary to know the difficulty of the review work. Various kinds of documents (mail, word, excel, PowerPoint, PDF, etc.) are handled according to the protocol for searching for different evidences for each lawsuit according to what kind of documents are to be probed and the policies / rules determined by attorneys. In reading and deciding whether it is evidence or not, the difficulty of reading the content written in the document and the length vary according to the document. Also, depending on the companies and industries that become parties to the lawsuit, the contents written are different.”

“Therefore, it is difficult to predict at how fast you can proceed with the review in advance, so you have to choose the model to charge the client based on the actual cost of the reviewer. However, if the speed of review can be kept at a certain speed by the natural language processing technology, and the difficulty of reading can be judged precisely in advance, the business model of charging by the number of documents will be established. In the current situation where the amount of data is growing steadily, charging by the number of documents which can accurately estimate the cost beforehand should be desirable for the client. Changing the model of pricing and charging in one industry is not easy, but if technology can realize it, it becomes a strong weapon. What I’d like to realize is to develop AI as a daily weapon of intellectual professional to bring about the philosophy of realizing fairness.”

CTO Hideki went on to elaborate patiently about KIBIT’s “landscaping” AI technology and the various innovative applications: “Many artificial intelligence in the world aims to become smarter by analyzing big data, but there is a need to ‘teach’ the artificial intelligence using a lot of data so that it can actually make effective judgment at the business site. However, there are many companies that do not have adequate data for teaching and practical application is difficult if machine learning does not proceed. Therefore, we have developed KIBIT which lets effective learning to take place with less data and solve customer’s problem. The most core technology among many artificial intelligence-related technologies implemented in KIBIT is ‘landscaping’. By extracting human tacit knowledge as a small scenery (a small number of teacher data), KIBIT can form the scenery of the unknown world and also connect to the outside as a single landscape view to learn human abstract judgment and construct knowledge of scale. Based on ‘behavioral information science’, we embody the data analysis know-how that we experienced as ‘behavior model’ making full use of sociology, criminal science and psychology, accumulate its know-how in a reusable manner, and realize highly accurate data analysis and unstructured data (such as electronic medical charts) analysis in a wide range of fields.”

“There are four main business areas in which KIBIT is used. The first one is legaltech to find and review litigation evidence in documents. The second is Business Intelligence, analyzing patents, VOC (voice of customers), etc., and contribute to business improvement. Third is digital communication, including the Kibiro robot which is active in corporate marketing activities, receptionists or showrooms and to make recommendations based on learned data. The fourth is healthcare. Let’s introduce these cases as an application of KIBIT to the healthcare field. (1) Falling Prediction System, (2) Development of medical devices enabling quantitative objective judgment of mental illness, (3) Early detection of worsening symptoms, (4) Cancer Individualization Medical AI system, (5) Pain Diagnosis Support AI System.”

“Falling prediction system is developed in collaboration with NTT East Japan Kanto Hospital from February 2015. The background to the development of this system was the problem that the risk of patients falling during hospitalization is increasing due to the increase in elderly people and is also evaluated by the JCI as one of the six major patient risk priority items internationally. In response to this issue, hospitals have taken actions to avoid the risk of falls, such as creating and assessing risk assessment sheets, substituting with safe footwear, controlling the amount of sleeping pills, measures which reduced the fall rate by 15%. However, since the above-mentioned efforts are not the original work of the nurse, the burden of the nurse has increased and a new problem has been created.”

“KIBIT analyzes the unstructured data in electronic medical record to predict the patient falling down and the accuracy is improved by about 50% compared with the conventional method such as Morse Fall Scale and STRATIFY. What most people don’t realize is the majority of the data in electronic medical record that’s valuable is unstructured data, the actual, free-form text that’s used by the doctors and nurses to really understand the whole of a patient which is a treasure trove of tacit knowledge. From half-trusting whether AI can find such a feature, the hospital was surprised at the results obtained, including predicting patients whom they thought were hard to understand. This fall prediction system will benefit the 1.32 million hospitalized patients. We want AI to become a good partner to notice tacit knowledge based on the intuition and experience of doctors and nurses.”

“In Jan 2017, we collaborate with Cancer Research Group on a Cancer Individualized Medical AI System that combines AI and genetic information analysis technology to provide precision medical treatment for each cancer patient. The project is planned to be completed in 2021 in five years. As part of collaborative research, we develop three types of systems using AI. The first is a diagnosis support system. We propose optimal treatment for patients based on patient information such as examination results by genome analysis, papers and medical information related to patient-appropriate treatment methods, etc. The Cancer Research Institute utilizes technologies, such as Clinical Sequence to comprehensively analyze genetic abnormalities in cancer patients and Liquid Biopsy to examine gene abnormality by blood test, and research methods for integrating and analyzing patient diagnostic data such as genome analysis information.”

“The second is an informed consent support system. The doctor adequately explains the medical condition and treatment policy and supports informed consent to obtain patient’s consent so that the situation can be explained to the most understandable level according to the patient’s answer. Third is an information support system which lets student doctors learn how experts select papers and medical information, and automatically select articles necessary for doctors based on the results. We also prepare an article that rewrites the article for the doctor for the patient so that we can select the necessary article automatically according to the patient. Unlike general artificial intelligence that learns by inputting an enormous amount of data regardless of whether it is useful or not, the technical advantage of KIBIT is that it produces good quality output by only learning a small amount of good quality data based on the tact knowledge made by learning expert judgment and sense. At the beginning system development will start with the focus mainly on lung cancer and breast cancer area. After that, we will adapt it to more cancer areas.”

“The development of medical devices that enable quantitative judgment of mental illness is a project adopted by Japan Medical Research and Development Organization (AMED). The patient’s facial expressions and voice and conversations are analyzed to get the multi-modal data, such as activities of daily living, to determine the severity of mood disorders and dementia by machine learning. In the mental disease area, there is a problem that there is no definitive biomarker. Therefore, in this project, a sensor device is placed between a doctor and a patient, and this sensor acquires multimodal data. By sending the acquired data to the cloud and analyzing the data, we adopt a mechanism to obtain comprehensive objective indicators.”

“Early detection of the deterioration of symptoms is a joint project with LITALICO, a company which supports employment of persons with disabilities. FRONTEO supports the employment support business of LITALICO to detect in advance the sign of symptoms worsening for those who have suffered from mental illness. LITALICO would find signs of worsening symptoms by checking support records by staff. However, there are thousands of them per day, and there are also individual differences in the power of staff to detect symptoms. It is also difficult to communicate tacit knowledge of experienced staff to young staff. Therefore, FRONTEO established a system that checks support records with KIBIT and notifies the staff that there is a predictor. Furthermore, the motivation of the staff improved as ‘I do not want to lose to artificial intelligence’ and the staff learns with the knowledge of KIBIT’s judgment criteria and the ability of the staff is up.”

“According to Japan Society of Chronic Pain, there are around 20 million people suffering from chronic pain. Diagnosis of pain is difficult to objectively evaluate using examination value. It depends on the experience and subjectivity of the doctor in charge. Especially for chronic pain which considers a combination of body abnormalities (biological factors) and stress environments (psychological and social factors), age, environment, social standpoint etc. In collaboration with Aichi Medical University and Nippon Organ Pharmaceutical, we are developing a Pain Diagnosis Support AI System to support appropriate medical treatment for improving chronic pain at an early stage. Aichi Medical University founded the first multidisciplinary therapeutic and research center in the field of pain and has specialized orthopedic surgeons, anesthesiologists, psychiatrists, nurses, physicists, therapists, clinical psychologists, working together on the clinical practice of chronic pain. The pain center provides treatment to nearly 7,000 people annually, and has achieved results such as improvement of pain which was not improved for a long time so far, and various knowledge in multidisciplinary medical care accumulates. However, the time and labor cost for examining one patient is very high as a result of the multidisciplinary examinations and chronic pain patients that are expected to increase in Japan’s super aged and stressed society. It is necessary to develop an epoch-making system that can efficiently and appropriately perform clinical practice.  We analyze the multidisciplinary clinical medical treatment data of Aichi Medical University’s interdisciplinary pain center with Concept Encoder to learn the diagnostic and therapeutic skills of the clinical chronic pain diagnosis team. By objectively analyzing such tacit knowledge with the artificial intelligence and scoring a new record by severity of chronic pain, it becomes a system to utilize for accurate diagnosis and transition to appropriate treatment leading to pain improvement as soon as possible.”

“In collaboration with second-hand car sales giant IDOM/Gulliver (TSE: 7599), we use KIBIT for Gulliver’s online customer service ‘Car Connect’ and provide automatic customer service support to users. KIBIT has already started an online hospitality service to select cars in consultation with advisers in chat in January 2016. It is not just a recommendation system, but also to propose an intention from the semantics in text data. In other words, I am trying to foster the satisfaction by context by ‘presenting the reason’ as to why it was recommended. This is because a person does not act if the content of the recommendation is merely ‘matching’ but ‘not convincing’. For example, the mind does not act if it’s just displaying a car that meets the requirements unless it is convinced that an attractive story is offered to me, while meeting the requirements. If you suggest intention in semantics and cooperate with external information, unexpected serendipity will be born, and you will be able to deal with more things than human beings. For example, it is natural for people who appreciate ‘Star Wars’ to recommend ‘Star Trek’. However, if KIBIT finds valid relevance from the context talking about ‘Star Wars’ and recommends ‘Kurosawa movies’, it is a serendipity created by AI. Therefore, KIBIT aims to make possible ‘artificial intelligence with humanity’.”

“An application example in modeling knowledge of experts with abundant product knowledge is KIBIT’s sales support at Mega Bank. In sales support for financial products, we have extracted and used useful information from a large amount of activity records such as daily reports, but there are limits to conventional keyword searching, and the number of reports that can actually be seen was limited. Therefore, in FRONTEO, the knowledge of product experts was learned as teacher data by artificial intelligence, and by creating some filters, we scored information according to the degree of relevance. As a result of prioritizing based on the scores, the load of looking for useful information was greatly reduced.”

“Another example is the scoring of the voice of customers (VOC) for a major apparel ecommerce company. Many VOCs were accumulated in the company, such as product review and customer inquiries from its EC site, inquiries to call center, etc. Because of the huge amount of data, it took time and effort to organize data for sending to other departments, such as product development. KIBIT automatically sorts and scores information by detailed viewpoints such as color pattern, fit, demand, comparison with other companies, etc., realizing the extraction of useful information and efficient classification compared with the conventional method. Also, since we can directly find wisdom leading to product improvement from the customer’s voice, we have been able to develop products that we could not work on until now. You can find and use the treasure contained in big data, and by using it well, we can truly respond to what the customers are requesting and to improve marketing measures.”

“Mitsubishi Heavy Industries makes use of KIBIT’s Knowledge Probe to improve the efficiency of investigation report preparation work aimed at grasping management judgment and industry trends.”
“Prior to using KIBIT, the company collects information posted in various news media, analyzes its contents, and summarizes it as a report for management. However, since it takes much time and effort to sort this collected information, it was a challenge that marketers with high skills cannot concentrate on new fields. Although attempting to construct a mechanism of extracting information using a programming language was tried, satisfactory results were not obtained. KIBIT automatically sorted out the huge amount of collected external news and Web media according to the purpose. This allowed marketers to focus on creating higher quality reports and adding value to analytical results and thinking with the time freed up. In order to solve this problem, Knowledge Probe learned the viewpoint of an experienced marketer. As a result, the time to extract a useful article was shortened to about half of the conventional time.”

“Bank of Yokohama, the largest regional bank, has made significant achievements in improving the efficiency of compliance checks. Under the Financial Instruments and Exchange Law, it is required to take appropriate measures in soliciting and contracting cases involving derivative transactions such as options and swaps and financial products. However, to that end, it is necessary to pay attention to the past transaction history, asset situation, customer’s age, etc. It is difficult to judge whether the content of the incident record with the customer stated by the salesperson is appropriate or not. Checking everything was a heavy burden to the administrator. Also, since the number of cases themselves is enormous, it was also an important task to prevent occurrence of blurring or leakage of judgment. KIBIT analyzed the occurrence of conflict with the Financial Instruments and Exchange Act based on the interactions written in the record with the customer. By scoring in the order of suspected possible compliance violations and other possibilities, we made it possible to efficiently discover transactions with high risk. As a result, compared with the previous checking method, the extraction efficiency of trading possibilities of conflicts is increased about 15 times. It was able to contribute to reducing litigation risk by early follow-up and by reducing the checking time of management staff. On 29 Nov 2018, we collaborated with Mitsui Information (MKI) to distribute and develop thee sales of KIBIT to financial institutions.”

“Another interesting case is the application to intellectual property business. When developing new products, it is necessary to investigate whether there is a patent similar to the technology developed by the company. However, the number of patent applications has been on an increasing trend year by year, and as the technology itself is becoming more sophisticated and complicated, it cannot be dealt with by human resources so far. Moreover, the traditional search method is a special skill by itself, not everyone can do it, and it takes a lot of time to read every single document retrieved. The high degree of accuracy of KIBIT demonstrates the enormous power in IP document investigation work which is indispensable when developing new products and in reducing work man-hour to about one fifth of conventional work.”

“In collaboration with Toyota Technical Development supporting the Toyota Group’s intellectual property strategy, we developed the patent research and analysis system ‘Patent Explorer’. By quickly discovering and extracting patent publications that intellectual property officers want to find from among survey targets by KIBIT, we realized an environment that enables efficient intellectual property work.  From the contents of the patent, we have expanded the range of applications by ourselves using new methods of use, such as technology trend survey investigating latest technical information.”

“KIBIT AI extracts the features and concepts related to the contents of the description of the patent rights to be invalidated, and then assigns a score indicating the respective level of proof to each piece within the enormous quantities of patent publications. Patent Explorer ranks the patent publication by score and provides the results through an easy-to-review user interface. In many cases, the evidence is contained within the top 1 percent, so a user can simply discover documents with a high level of proof by only reviewing a small volume of documents, even when lacking specialist expertise. For example, in the case of a search of 3,000 patent publications, the appropriate evidence can be found by reviewing only a few dozen publications ranked at the highest levels. Patent Explorer is therefore a powerful AI-based system that supports corporate patent strategies and has already been installed by over 50 companies. The patent technology areas cover a wide range of industries, particularly large manufacturers for which patents are important, such as in the chemicals & materials, machinery, manufacturing and food & beverage sectors.”

“FRONTEO has generated significant interest from large Japanese and foreign companies who attended the 2018 Patent Information Fair & Conference held in Japan from November 7-9. Consequently, we plan to expand sales not only in Japan but also in the U.S. and other global markets. We are now offering an inexpensive, easy-to-introduce entry plan to a small number of user accounts. This is in response to our clients wanting to improve the efficiency of their patent search operations by using AI. The plan keeps the cost to one-third of the usual monthly license fee, to cater to clients who first want to give it a try. In addition, Patent Explorer19 technology will soon be applied beyond patent search to improve the efficiency of litigation document review, which is one of FRONTEO’s strengths. Following the major trend toward open innovation and AI, we are confident that Patent Explorer19 will continue to expand and be implemented widely and globally.”

CEO Morimoto summed up on FRONTEO’s philosophy to bring about the realization of “Bright Value” and motto of “Enthusiasm, Persistence and Impression” as his driving force personally and for everyone at FRONTEO: “What we mean by ‘Bright Value’ is to securely identify risks and opportunities buried in records. With our frontline technology built on the knowledge, experience and judgment of experts, we provide solutions optimized to securely identify risks and opportunities that are buried in records. Value is brought on by realizing a fair society where the most needed and most appropriate information are accessible and discoverable to all, in legaltech, healthcare, finance, intellectual property, education, human resources and other areas. Our motto ‘Enthusiasm, Persistence and Impression’ was chosen to motivate our team to persevere in committing to our shared mission to bring about the realization of bright value. What drives you is passion. You cannot accomplish anything without it. However, passion means nothing if it is a fleeting one; you must also have perseverance to overcome any obstacles that may arise. Once you accomplish your goal, there is joy, revelation and inspiration upon reflecting how much you have grown from this endeavor, and for the first time, you are able to move those around you.”


Intrigued and want to read more? Download this week’s H.E.R.O. HeartWare: Weekly Asia Tech News with brief highlights of the inspiring entrepreneurial stories of tech leaders in Asia whom we have been monitoring over the past decade in our broader watchlist of over 300 listed Asian tech companies and our focused portfolio of 40 HERO Innovators who reveal their problems and successes behind building the company. Inspired by Brandon Stanton’s photo-journalistic project Humans of New York which collects and highlights the street portraits and moving stories of people on the streets around us who were doing things that changed lives and made a difference in the city but often went unnoticed, we have curated a collection of Hear the Heart of the H.E.R.O. stories on our website which we aim to update with refreshing and uplifting new stories weekly. Please check them out and give us your valuable feedback so that we can improve to make them better for you.


It started with rethinking a few questions. Question No. 1: Can the megacap tech elephants still dance? Or is this the better question: Is there an alternative and better way to capture long-term investment returns created by disruptive forces and innovation without chasing the highly popular megacap tech stocks, or falling for the “Next-Big-Thing” trap in overpaying for “growth”, or investing in the fads, me-too imitators, or even in seemingly cutting-edge technologies without the ability to monetize and generate recurring revenue with a sustainable and scalable business model? How can we distinguish between the true innovators and the swarming imitators?

Question No. 2: What if the “non-disruptive” group of reasonably decent quality companies with seemingly “cheap” valuations, a fertile hunting ground of value investors, all need to have their longer-term profitability and balance sheet asset value to be “reset” by deducting a substantial amount of deferred innovation-related expenses and investments every year, given that they are persistently behind the innovation cycle against the disruptors, just to stay “relevant” to survive and compete? Let’s say this invisible expense and deferred liability in the balance sheet that need to be charged amount to 20 to 30% of the revenue (or likely more), its inexactitude is hidden; its wildness lurks and lies in wait. Would you still think that they are still “cheap” in valuation?

Consider the déjà vu case of Kmart vs Walmart in 2000s and now Walmart vs Amazon. It is easy to forget that Kmart spent US$2 billion in 2000/01 in IT and uses the same supplier as Walmart – IBM. The tangible assets and investments are there in the balance sheet and valuations are “cheap”. Yet Kmart failed to replicate to compound value the way it did for Walmart. Now Walmart is investing billions to “catch up” and stay relevant. Key word is “relevancy” to garner valuation.

We now live in an exponential world, and as the Baupost chief and super value investor Seth Klarman warns, disruption is accelerating “exponentially” and value investing has evolved. The paradigm shift to avoid the cheap-gets-cheaper “value traps”, to keep staying curious & humble, and to keep learning & adapting, has never been more critical for value investors. We believe there is a structural break in data in the market’s multi-year appraisal (as opposed to “mean reversion” in valuation over a time period of 2-5 years) on the type of business models, the “exponential innovators”, that can survive, compete and thrive in this challenging exponential world we now live in. Tech-focused innovators with non-linear exponential growth potential are the most relevant multi-year investment trend and opportunity.  

During our value investing journey in the Asian capital jungles over the decade plus, we have observed that many entrepreneurs were successful at the beginning in growing their companies to a certain size, then growth seems to suddenly stall or even reverse, and they become misguided or even corrupted along the way in what they want out of their business and life, which led to a deteriorating tailspin, defeating the buy-and-hold strategy and giving currency to the practice of trading-in-and-out of stocks. On the other hand, there exists an exclusive, under-the-radar, group of innovators who are exceptional market leaders in their respective fields with unique scalable business models run by high-integrity, honorable and far-sighted entrepreneurs with a higher purpose in solving high-value problems for their customers and society whom we call H.E.R.O. – “Honorable. Exponential. Resilient. Organization.”, the inspiration behind the H.E.R.O Innovators Fund, (surprisingly) the only Asian SMID-cap tech-focused fund in the industry.

The H.E.R.O. are governed by a greater purpose in their pursuit to contribute to the welfare of people and guided by an inner compass in choosing and focusing on what they are willing to struggle for and what pains they are willing to endure, in continuing to do their quiet inner innovation work, persevering day in and day out. There’s a tendency for us to think that to be a disruptive innovator or to do anything grand, you have to have a special gift, be someone called for. We think ultimately what really matters is the resolve — to want to do it, bring the future forward by throwing yourself into it, to give your life to that which you consider important. We aim to penetrate into the deeper order that whispers beneath the surface of tech innovations and to stand on the firmer ground of experience hard won through hearing and distilling the essence of the stories of our H.E.R.O. in overcoming their struggles and in understanding the origin of their quiet life of purpose, who opened their hearts to us that resilience and innovation is an art that can be learned, which can embolden all of us with more emotional courage and wisdom to go about our own value investing journey and daily life.

As the only Asian SMID-cap tech-focused listed equities fund in the industry, we believe we are uniquely positioned as a distinctive and alternative investment strategy for both institutional and individual investors who seek to capture long-term investment returns created by disruptive forces and innovation without herding or crowding to invest in the highly popular megacap tech stocks, and also provide capital allocation benefit to investors in building optionality in their overall investment portfolio.

The H.E.R.O. HeartWare Weekly highlights interesting tech news and listed Asian emerging tech innovators with unique and scalable wide-moat business models to keep yourself well-informed about disruptive forces and innovation, new technologies and new business models coming up, and the companies that ride on and benefit from them in some of the most promising areas of the economy in Asia as part of our thought leadership for our ARCHEA Asia HERO Innovators Fund to add value to our clients and the community. Hope you find the weekly report to be useful and insightful. Please give us your candid feedback and harshest criticisms so that we can improve further to serve you better. Besides the BATTSS (Baidu, Alibaba, Tencent, TSMC, Softbank, Samsung), do also tell us which Asian tech entrepreneurs & CEOs whom you admire and respect and why – we will endeavor to do up profiles of them for sharing with the community. Thank you very much and have a beautiful week ahead.

Warm regards,
KB | kb@heroinnovator.com | WhatsApp +65 9695 1860
www.heroinnovator.com

H.E.R.O.’s Journey in Tech (26 January 2019) – Software Stocks Can Work In Good or Bad Times + When Charlie Munger Calls, Listen and Learn

H.E.R.O.’s Journey in Tech (26 January 2019) – Software Stocks Can Work In Good or Bad Times + When Charlie Munger Calls, Listen and Learn

Companies

  • Grainger eyes mid-size companies as it invests more in Zoro.com; “Our single-channel businesses, mainly MonotaRO and Zoro, continue to drive profitable growth” (DC)
  • Trend Micro launches regional AMEA HQ in Singapore; deepens region’s cyber capabilities (NWA)
  • Rakuten’s package delivery drones to take flight soon; Rural areas in Japan would be serviced, but cost is a concern (Nikkei)
  • Koh Young to Demo Hermes and CFX Lines at IPC APEX EXPO 2019 (iconnect)
  • Taiwan’s Delta Electronics eyes Krishnagiri for Rs 4,000 electronic plant (NIE)
  • Afterpay’s quest to be the global platform connecting retailers with Millennials (AFR)
  • How AfterPay and Pro Medicus show why you must buy founder-led companies (MF)
  • Mukesh Ambani wants to be India’s first internet tycoon; Thanks to his ambitions, Indians are getting online faster than ever (Economist)

BATTSS – Baidu, Alibaba, Tencent, TSMC, Samsung, Softbank

  • Consumption remains engine and driving force for China’s growth, Alibaba CEO says (SCMP); ‘Distorted’ private tech market valuations to see correction in next six to nine months, says Alibaba’s Joe Tsai (SCMP)

FAANNMG – Facebook, Amazon, Apple, Nvidia, Netflix, Microsoft, Google

  • Facebook Has Got the Wrong Kind of Friends; Facebook’s user base is growing, but it may be shrinking where it matters (WSJ)
  • Zuckerberg to integrate WhatsApp, Instagram and Facebook Messenger: NYT (Reuters); Why Facebook Can’t Resist Integrating WhatsApp; The decision to unite its empire is both an inevitable end to independence for its disparate properties, and a barrier against calls for a breakup. (Bloomberg)
  • Facebook knowingly duped game-playing kids and their parents out of money (Reveal)
  • Where Amazon Returns Go to Be Resold by Hustlers; Welcome to the abyss of the “reverse supply chain,” where hope springs eternal. (Atlantic)
  • Brands Invent New Lines for Only Amazon to Sell; Amazon gets exclusive products, while brands receive faster customer feedback, marketing support and increased sales (WSJ)
  • Startups Find It Easy To Let Alexa Speak On Their Behalf (CB)
  • DeepMind’s AlphaStar Reminds Us That AI Is Still Dependent On Human Creativity (Forbes); DeepMind AI Beats Professional Human StarCraft II Players (Forbes)
  • Why Microsoft Is the ‘Best-Positioned Firm in Tech’ (Barron’s)
  • How NVIDIA Built A Record-Breaking AI Supercomputer In Under 3 Weeks (Forbes)
  • Netflix setting bad example for China’s video streamers; Losses widen amid content arms race but platforms will struggle to retain subscribers (FT)
  • Nvidia’s “Kitchen Manipulator” Robot Uses AI To Cook Meals (ZH)

Asia Tech & Innovation Trends

  • Bytedance’s WeChat rival Duoshan hits 1 million downloads (Technode)
  • Meet the little-known Chinese Wi-Fi startup that rubs shoulders with WeChat and Alipay; The app that gives people free Wi-Fi has 800 million monthly active users worldwide (TC)
  • Fundraising by China’s startups surges to $80bn (Nikkei)
  • Lessons from the fall of China’s bike-sharing pioneer; Ofo’s young founder is banned from pricey hotels and first-class flying (Economist)

Global Tech & Innovation Trends

  • Software Stocks Can Work In Good or Bad Times (Barron’s)
  • Slack faces growing challenge from Microsoft; Stewart Butterfield, the entrepreneur who founded Slack, faces renewed competition with Microsoft’s Teams (FT)
  • Automakers may have completely overestimated how many people want electric cars (qz)
  • IPO Hopes Trigger Scramble for Shares of Top Unicorns; But transactions are hard to track and some questionable practices have arisen (WSJ)
  • Tesla Should Pull an Apple: Leave ‘Production Hell’ to Other People; The real money isn’t in building beautiful things. It’s in creating them. (WSJ)
  • Dell May Be Unloved Right Now, but Its VMware Stake Is a Silver Lining (Barron’s)
  • Humans Question Their AI-Based Future; Smart machines are now being applied to activities requiring intelligence and cognitive capabilities (WSJ)
  • Over 70 nations agree to hammer out global rules for e-commerce; China joins effort led by the US, EU and Japan despite opposing free data flow (Nikkei)
  • When do AI-related inventions merit a patent? (SCMP)
  • The myth of uber for x (II)
  • 3D Vision Enhancing Robot Opportunities (EE Times)

Life

  • When Charlie Munger Calls, Listen and Learn (WSJ)
  • The Era of “Move Fast and Break Things” Is Over; What systemic, societal change do you aspire to create with your product? “Minimum viable products” must be replaced by “minimum virtuous products” (HBR)
  • Eugene Wei – Tech, Media, and Culture – [Invest Like the Best, EP.117] (IFG)
  • Howard Schultz Teaches You How To Be A Leader In A Crisis (Forbes)
  • Sam Altman: How To Be Successful (Sam Altman)
  • Why We Worry (and How to Stop) (Medium)
  • The 1800-year-old handbook for a “tranquil flow of life” (Medium)

H.E.R.O.’s Journey in Tech (25 January 2019) – Michael Cannon-Brookes snr: How I raised a son who became Atlassian billionaire + Susan Cain – How to Overcome Fear and Embrace Creativity (#357)

H.E.R.O.’s Journey in Tech (25 January 2019) – Michael Cannon-Brookes snr: How I raised a son who became Atlassian billionaire + Susan Cain – How to Overcome Fear and Embrace Creativity (#357)

Companies

  • Meituan to invest $1.7 billion in push to digitize merchant partners (Technode)
  • Michael Cannon-Brookes snr: How I raised a son who became Atlassian billionaire (AFR)

BATTSS – Baidu, Alibaba, Tencent, TSMC, Samsung, Softbank

  • Latest WeChat update hints at its ‘operating system’ ambitions (Technode)
  • Entrepreneurs should focus on the problem, not the technology, says Alibaba’s Joe Tsai (SCMP)

FAANNMG – Facebook, Amazon, Apple, Nvidia, Netflix, Microsoft, Google

  • Facebook Slides After Report Claims 50% Of Its Users Are Fake (ZH)
  • AWS launches Neo-AI, an open-source tool for tuning ML models (TC)
  • The prime challenges for Amazon’s new delivery robot (Wred)
  • Amazon Can’t Fix Facial Recognition; Companies lack incentives to stop the creepiness. (Bloomberg)
  • Amazon offers cautionary tale of AI-assisted hiring (FT)
  • Apple Self-Driving Car Layoffs Are a Nod to Reality; It was never clear that Apple managed to develop the partnerships it needed. Now it should focus on the bets it can win. (Bloomberg)
  • Google’s StarCraft-playing AI is crushing pro gamers (CNN)

Asia Tech & Innovation Trends

  • Quasi-unicorn IceKredit aims to leverage AI in becoming China’s FICO (Technode)
  • Bing, Baidu and a Big Mess for Chinese Search Engines; Internet users are wondering why Microsoft-owned Bing is suddenly inaccessible in China. The sector faces some even bigger questions. (WSJ)
  • Japanese firms hopping on ride-hailing bandwagon in Southeast Asia (JT)
  • Korea is home to 6 unicorn startups: Coupang, Bluehole, Yello Mobile, Woowa Brothers, L&P Cosmetics and Viva Republica (Investor)
  • “We’re seeing $2.5b for food delivery in Indonesia alone”: Go-Jek on transaction value, international expansion, and IPO plans (KRA)
  • Go-Jek makes first close of $2 billion round at $9.5 billion valuation (TC)
  • In the business of improving other businesses: Malaysia’s game-changers in the B2B spectrum (e27)

Global Tech & Innovation Trends

  • Heathrow Turns to AI to Cut Gap Between Flights by 20 Seconds (Bloomberg)
  • Blue Prism looks to partners to expand robotic process automation with AI (TC)
  • Top 10 US subscription video apps pulled in $1.3B last year, a 62% increase from 2017 (TC)
  • How Uber Eats’ Starbucks delivery deal changes the American delivery wars (TN)
  • Are Consumers Ready To Buy And Sell Homes Online? (PYMNTS)
  • Instacart CEO reaffirms IPO is ‘definitely’ on the horizon (CNN)
  • Palo Alto Networks Stock to Rally on Rising Security Spending, Analyst Says (Barron’s)
  • Fog, Edge Networks Merge in IoT (EE Times)
  • Dutch AI Startup Wants to Reveal the Real Value of Your Property (Bloomberg)
  • Weak Intel outlook stokes fears of a chip slowdown (Reuters)

Life

  • Susan Cain – How to Overcome Fear and Embrace Creativity (#357) (Tim Ferris)
  • Billions to Bust: Lessons from the failure of some of India’s biggest business names. (BT)
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