Presentation Material for FY04-2021 Q3

Notice

This document is an excerpt translation of the original Japanese document and is only for reference purposes. In the event of any discrepancy between this translated document and the original Japanese document, the latter shall prevail.

Presentation Material for FY04/2021 Q3 Financial Results

March 12, 2021

HEROZ, Inc.（4382）

1. Business Overview

• 2. FY04/2021 Q3 Performance

• 3. Growth Strategy

• 4. Reference Materials

Name

HEROZ, Inc.

Location

PMO Tamachi 2F, 5-31-17 Shiba, Minato-ku, Tokyo

Established April 2009

Representatives Takahiro Hayashi/Tomohiro Takahashi

Business

AI (B-to-B) services: HEROZ Kishin

Description AI (B-to-C) services: "Shogi Wars", etc.

Membership Japan Deep Learning Association,

The Japanese Society for Artificial Intelligence

2019

Listed on the First Section of Tokyo Stock Exchange (TSE)

2018

Listed on Tokyo Stock Exchange (TSE) Mothers

Capital and business alliance with Netmarble Games Corporation

2017

Capital and business alliances with Takenaka Corporation and Koei Tecmo Games

2016

Capital and business alliance with Bandai Namco Entertainment

2013

Shogi AI, developed by HEROZ engineers, defeated a shogi professional

2012

Launched mobile app, "Shogi Wars"

Representative Director and CEO

Takahiro Hayashi

Graduated from Waseda University Joined NEC as a technology engineer Experience at IT strategy division, business planning division

Founded HEROZ

Representative Director and COO

Tomohiro Takahashi

Graduated from Waseda University Joined NEC as a technology engineer

Experience at Business Planning Division, BIGLOBE Founded HEROZ

Shogi Track Record

Amateur 6th dan (highest rank after becoming national amateur champion)

7th dan, Shogi Wars

Amateur Kisen Champion (7-time title defender as national champion)

Played against Yoshiharu Habu (permanent 7 title holder)

Our Vision

Creating the future through

artificial intelligence (AI)

revolutions

Chess AI

Shogi AI

Go AI

Deep Blue ('97) defeated a professional Chess player

IBM

AI developed by our engineers defeated a professional Shogi (Japanese Chess) player ('13)

Google acquired Deep Mind ('14)

AlphaGo, developed by Deep Mind, defeated a professional Go player ('16)

Google

B-to-B Services: Machine Learning by Replacing Shogi Game Records with Other Data

Structural design data, financial data, etc.

Provides models, developed by machine/deep learning, as a service

Client's data sent to HEROZ

Kishin/model developed by machine learningOutput after machine learning through deep learning, etc.

Output applied in business settings

Research/develop Shogi AI

Standardize AI technology accumulated through shogi AI

Establish "HEROZ Kishin"=MLaaS

（Machine Learning as a Service）

Establish an infrastructure which allows HEROZ to provide AI services efficiently to solve various challenges in various industries just by changing input dataProvide comprehensive AI services with massive servers

Achieve stable, sustained earnings and high switching costs

Output precision increases through repeated machine learningEarning structure: initial setup fee and ongoing fees

B-to-B Services: Engines included in HEROZ Kishin and Examples of Applications

◼ Create AI products by combining engines and achieve an efficient operating structure

We aim to create the industry standard for AI in each sector through collaboration with companies which own high-quality private data

◼ Focusing on construction, finance, and entertainment for the foreseeable future

◼ Earning structure is initial setup fee and ongoing fees

*Examples of clients served

Enter-tainment

Charging fees for B-to-C content which user AI

• ◼ Leveraging AI-related technology to provide mind games such as shogi, chess, and backgammon worldwide

• ◼ Shogi Wars has remained cash cow backed by increase of paid users on a YoY basis

• ◼ Staying home by COVID-19 and shogi event held on our mobile app led to increased demand for our app, with an increase in our paid active user base

Shogi Wars

1. Business Overview

2. FY04/2021 Q3

Performance

• 3. Growth Strategy

• 4. Reference Materials

◼ We believe that EBITDA, as calculated below, is our key performance indicator

EBITDA = Operating Profit + Depreciation/Amortization

Expenses

◼ In AI-related businesses, server investments, etc. are required to engage in advanced machine learning, leading to various depreciation/amortization expenses. We aim to continuously enhance enterprise value/equity value via EBITDA growth, without being concerned about fluctuations in one-time depreciation/amortization expenses.

◼ We update our assumptions regarding the new coronavirus infection to estimate earnings forecast as follows, but have not revised our earnings forecast announced at the beginning of this fiscal year

Updated assumptions to estimate earnings forecast

• • The increase in COVID-19 patients will continue in the second half as well

• • Growth will slow down in the entire fiscal year by slowdowns in progress of projects and reduced opportunities for sales discussions due to emergency declared by the government

↑：Positive Impact ↓：Negative Impact →：Non-material Impact ※ Our earnings forecast has not been changed since the beginning of this fiscal year

• ◼ Revenues increased in Q3 on a year-on-year basis backed by growth of AI (B-to-C) although AI (B-to-B) services decreased due to emergency declared for COVID-19

• ◼ EBITDA and other profits made steady progress towards achievement of fiscal year forecasts while they decreased on a year-on-year basis. We have been investing proceeds from public offering in December 2019 for our medium-to-long term growth

Q1-Q3 ActualNet Sales

1,127

1,121

+0.5%

1,700 66.3%

EBITDA*

258

372

EBITDA Margin

22.9%

33.2%

Operating Profit

215

324

△30.6% － △33.7%

290 89.0%

17.1%

230

- 93.5%

Operating Margin

19.1%

28.9%

Ordinary Profit

Net Income

206 140

270 184

－ △23.5% △23.7%

13.5%

-220 93.9%

150 93.8%

* EBITDA = Operating Profit + Depreciation Expenses + Amortization of Lease Deposits

• ◼ Net sales of AI (B-to-B) services, the core pillar of our growth strategy, declined in Q3 due to reduced opportunities for business meetings by COVID-19

• ◼ Net sales of AI (B-to-C) services increased compared with the previous fiscal year led by

  "Shogi Wars"

(Units: JPY millions)

FY04/2017

FY04/2018

FY04/2019

FY04/2021 Q1-Q3

Net Sales（BtoB）

Net Sales（BtoC）

EBITDA

EBITDA margin

• ◼ Labor cost has increased on a year-on-year basis and is expected to keep growing next fiscal year as well to increase our engineering capacity, which will lead to our medium-to-long term growth

• ◼ In addition, there were an increase in app commission fees by growth of AI (B-to-C) services, and anticipatory investments of proceeds via public offering for our growth strategy. Although profits were down compared with the previous year, they are in line

FY04/2018

FY04/2019

FY04/2020

FY04/2021 Q1-Q3

labor costdepreciation costapp commission feesadvertisement expensesothers(COGS/SG&A)

◼ B/S remains strong backed by cash and deposits increased via public offering in 2019

◼ We plan to invest them in efforts to achieve the medium-to-long term growth strategy

(e.g. hiring for AI engineers, in-house computing servers and external cloud computing services, investments to companies with peripheral technologies which can be applied to our operations, working capital

Units: JPY millions

As of 1/31/2021

(Reference) As of 4/30/2020

Current Assets

5,990 5,935

Cash and deposits Fixed Assets

5,805 5,562

480 473

Property, plant and equipment Intangible assets Investments and other assets

160 131

5

６

315 334

Total Assets

6,471 6,408

Current Liabilities Fixed Liabilities Net Assets

135 226

- 6,336

- 6,182

• 1. Business Overview

• 2. FY04/2021 Q3 Performance

3. Growth Strategy

4. Reference Materials

• ◼ We aim to achieve EBITDA growth by investing our cash flows and leveraging our know-how from our AI (B-to-C) services to our AI (B-to-B) services, which are positioned as our key medium-to-long-term pillar of growth

  EBITDA

• ◼ In our AI (B-to-B) services, we aim to achieve more projects in the initial setup fee phase, to complete development as rapidly as possible, and to

• ◼ Domestic DX (digital transformation) is expected to accelerate due to the future decrease in the working population as well as the impact of the COVID-19 pandemic

• ◼ AI allows for DX of a wide variety of operations including those involving decision- making, which were previously considered difficult to automate

◼ DX will begin with standard tasks based on

Standard Decision- Creative structured data and is expect to expand to decision-

Tasks making Tasks, etc.

Structured data

Unstructured data

making and tasks which utilize unstructured data

◼ Our AI can automate a wide variety of operations including those requiring decision-making. We have also achieved DX for unstructured data, which were traditionally considered difficult for DX

TraditionalOur AI

IT

◼ We are promoting DX and building a track record in

areas including construction, finance, and

entertainment

◼ Joining the " SDGs for Regional Revitalization Public-Private Partnership

Platform"

• ◼ On December 2, 2020, we joined the " SDGs for Regional Revitalization Public-Private Partnership Platform" established by the Cabinet Office. The platform was established as a forum for public-private partnerships to deepen partnerships with a wide range of stakeholders with the aim of promoting domestic implementation of the SDGs and further local development.

• ◼ Through our participation in the platform, we will promote solutions to regional issues in collaboration with a wide range of stakeholders, and contribute to the promotion of regional development driven by the SDGs

• 1. Business Overview

• 2. FY04/2021 Q3 Performance

• 3. Growth Strategy

4. Reference Materials

◼ We believe there is also significant potential demand for enhancing operational efficiency through AI in the construction industry, which is one of our areas of focus

◼ Over 1/3 of first-class registered architects are over 60 (average: 56.2 years old)

(source: Report on Construction-related Administration Aimed at Securing Safety of Architecture, Social Infrastructure Council, August 2016)

◼ The number of construction and mining industry workers is expected to decrease from 5.05 million in 2014 to 4.16-4.24 million in 2030, with some variability depending on future economic growth and labor market participation trends (source: JILPT, 2015 Estimated Labor Supply/Demand)

◼ We entered into a capital and business alliance with Takenaka Corporation in 2017 and became a member of i-Construction. We aim to create the industry standard AI for the construction industry, enhancing productivity and creating a new, attractive construction site

◼ Potential AI demand in Japan can be expected to be among the largest worldwide, as the working population is expected to decrease significantly going forward

Projection of Population Age 15-64

140

120

100

80

60

40

20

(Median Prediction Interval, 2020=100)

About 28%decrease by about 11% and about 28%

0

22002200年

22002255年

2030年

全Gl世ob界al

2035年 22004400年 20240545年 22005500年 20250555年

中Ch国ina

Source: Prepared by HEROZ based on United Nations, World Population Prospects, The 2019 revision

from 2020 to 2035 and by about 21% from 2020 to 2055. On the other hand, the working population is expected toduring the same periods, respectively

◼ Based on such forecasts, the Japanese working population will show the largest decrease among leading GDP nations

• ◼ We continue to promote efforts to prevent the spread of COVID-19 and prioritize health and safety of our stakeholders including our employees

• ◼ There is no significant impact on operations and labor productivity

～April 2020

May

June～

・Introduced a selective system for work from home and flexible hours in February

Internal possible, in April

・All officer and employees were

・Set up an internal consultation desk for COVID-19

・Improved the work from homeenvironment through reinforcement of wide meeting VPN (virtual private network)

・Continue an optional system for work from home and flexible hours ・Promote an internal DX to improve our work productivity

Disclaimer

The contents set out in this material are prepared based on generally acknowledged economic, social and other conditions, and on certain assumptions deemed rational by HEROZ, Inc. and may therefore be subject to change without prior notice due to changes in the managerial environment or for other reasons.

The forward-looking statements set out in this material including performance outlooks are based on information currently available to HEROZ, Inc. and on certain assumptions deemed rational, and may therefore differ materially from actual results due to uncertainties in judgements or assumptions, or for other reasons.

Such factors of uncertainty and change include both general, domestic and international economic conditions, such as general industry and market conditions, interest rates, and foreign exchange fluctuations. HEROZ, Inc. shall not undertake any obligations to update or revise any forward-looking information set out in this material even in the event that new information becomes available or certain events occur hereafter.

This material is an excerpt translation of the original Japanese material and is only for reference purposes. In the event of any discrepancy between this translated material and the original Japanese material, the latter shall prevail.