OSA DC Rating Review
|Start ICO||21 Jul 2018|
|End ICO||31 Aug 2018|
We assign OSA DC a “Stable+” rating.
The Optimal Shelf Availability Decentralized Platform (OSA DC) is a decentralized platform, which is the further development of the currently functioning OSA Hybrid Platform (OSA HP). The OSA DC project will seek to unite producers of goods, suppliers, sellers and buyers in one ecosystem in order to solve the biggest problem in global retail sales - the optimum availability of goods on the shelves, providing a 5% increase in sales volume and a 150-450% ROI for the participating businesses.
As for the strengths of the project, we note that the use of advanced technologies, such as artificial intelligence, machine learning, augmented reality, blockchain and smart contracts, will provide high-quality digital services for all participants of the ecosystem and protect the data of each participant in the supply chain from manipulation and unauthorized access. The OSA Hybrid Platform has already integrated almost 2,500 stores and it is used by eleven manufacturers of consumer goods, including brands such as Coca-Cola, Mars, Danone, L’Oréal and METRO. The OSA DC project will aim to partner with AI in medicine and health protection and will combine consumers health tracking data with recommended products. The OSA DC project is entering the emerging market of complete chain-of-custody tracking and product control, which increases the chances of occupying a certain market share.
In terms of weaknesses of the project, we note that the token distribution structure, according to the results of the ICO, provides for the possibility of entering the market with the number of tokens 3 times higher than the volume of the primary placement. This ICO structure gives more chances for the growth of tokens in the short-term than after the lock-up period. We also note that the OSA DC team is too dependent on its partners in the development of its business and this dependence may ultimately lead to a delay in the launch of a fully functional product.
Based on the facts above, as well as the conducted analysis of the market, the competitive environment, and the level risk for the scope and the project itself, we decided to assign the project a “Stable+” rating.
OSA Decentralized (OSA DC) is designed to create value for consumers, retailers and manufacturers through digital services based on artificial intelligence. OSA DC is built on existing HP OSA technologies - big data platform, machine learning and real-time data processing. The ecosystem will be built on the OSA DC platform that will bring together supply chain participants, data providers, scientists, IT professionals, application developers and providers of computing resources.
Smart contract platform: Blockchain Ethereum
Contract type: ERC20
Token: Optimal Shelf Availability Token (OSA)
Accepted currencies: ETH, BTC, LTC, BCH, ETC
The total number of tokens issued is 2,285,714,285. There will be 514,285,714 tokens available for sale. There is no additional emission. Tokens for the reserve fund, team and consultants will amount to 1,771,428,571 and they will be blocked for 12 months.
All tokens not sold during the ICO will be burned.
Soft cap: no
Hard cap: $40m
Token price: OSA = 0.0002 ETH
Minimum purchase amount: 1 ETH
The distribution structure of the issued tokens is as follows:
Private Pre-sale, Whitelist registration opened (over):
Start date: March 20th, 2018
End date: March 21st, 2018
Start date: May 21st, 2018
End date: June 21st, 2018
There is a bonus program for the Public Pre-sale:
Start date: July 21st, 2018
End date: August 21st, 2018
The Public Sale stage provides a bonus of up to 6%.
The funds raised in the Token Sale will be distributed as follows:
Description of the Project Services
Currently, the project uses the OSA Hybrid Platform operational platform and OSA DC is the further development of the current platform with additional B2C and B2B functions.
Key features of the OSA DC ecosystem:
- Blockchain technology and smart contracts ensure the transparency and consistency of the data: customer feedback, information on the composition of the product, expiration dates, ingredients, storage and transport conditions of the product through the supply chain, and store shelves until the end user receives the product. A set of sensors is used to monitor the movement and storage conditions of products. The data from the set is stored on blockchain.
- If there are inconsistencies (the absence of goods on the shelf or in the warehouse, goods past their expiration date, the recognition of damaged packaging, etc.), the platform sends alerts to employees to solve any problems.
- The monitoring, analysis and sales forecasting of each product in stores with the use of AI, Machine Learning and Image Recognition. Sales forecasting includes the collection of various data on the product such as consumer demand, availability in the warehouse, advertising campaigns in other stores, availability of substitutes and complementary goods, etc. The ultimate goal is to ensure the optimal availability of goods on the shelves, excluding their excess or shortage.
- The user interface will allow interaction with the platform services (currently a web interface is used, there are plans for later on to develop and launch mobile versions for iOS and Android, Windows and Mac OS applications and chatbots for Facebook, Messenger and Telegram). The platform services include:
- A catalog for the search of goods with the necessary characteristics (for example, products for pregnant women, for children, products without artificial additives, diet products and so on) from suppliers and retail companies in which the platform is integrated. The catalog will also include images of each product, its size and composition, rating information and customer reviews.
- The user can leave feedback and rate the products. This data will be processed via machine learning using game theory to find false reviews.
- The user can take a picture of the goods on the shelf using a smartphone, and the augmented reality function selects the products the user needs based on the applied filter.
- Receiving notifications about problems with delivery of goods to the store.
- Each personal digital AI assistant will be able to accumulate and study the preferences of each user on the basis of their previous purchases to shorten the amount time of spent searching for interesting products.
- Built-in business intelligence tools (business intelligence tools will be provided by third-party solutions with which the platform is integrated are also available).
- The data warehouse will store both source data collected from various sources (retailers, manufacturers and third-party data providers) and the resulting analytics. The provision of computing power will be done via outsourcing.
The following parameters are evaluated when a new store wants to connect to the platform:
- Catalog of products sold.
- Catalog of product categories.
- Catalog of shops.
- History of sales data for the last two years.
- Data on the supply chain.
- Current sales data updated every 10-60 minutes.
All of this data is transmitted over a secure API in OSA DC for evaluation. Then, a pilot version of the product is launched, which includes setting up machine learning algorithms and AI data processing. KPI measures the results of the pilot project. If the results do not meet the requirements, the pilot project will undergo an additional cycle of adjustment and calibration. If the evaluation is positive, the platform is integrated into the entire retail network of the client.
According to the Whitepaper, nearly 2,500 stores are integrated into the OSA Hybrid Platform and eleven manufacturers of consumer products are already using the platform, including Coca-Cola, Mars, Danone, L’Oréal, JTI, METRO and others.
In our opinion, the existence of a working platform and the benefits that it offers to all of its participants, as well as the fact that the platform is currently being used by major producers of consumer goods and retail chains, give us reason to believe that such a product will be in demand.
In recent years, both the manufacturers of goods and sellers have had more opportunities to monitor and analyze the behavior of buyers through various sensors and cameras due to the development of AI and ML. The data collected in this way can influence the layout of the store, marketing, sales and customer preferences for a more personalized shopping experience.
It is expected that the market of analytical technologies in retail stores will grow, as more and more sellers introduce tracking and analytics technologies. According to Tractica, the world revenue from hardware, software and video analytics services will grow from $858m in 2015 to $3bn in 2022, equivalent to a CAGR of 19.6%.
According to the report, the market for using computer vision will develop in the following directions:
- Video surveillance.
- Optimization of real estate development.
- Facial recognition.
- Inserting ads into images and videos.
- Analysis of human emotions.
- Conversion of paper documents to digital.
- Localization and comparison.
- AR and VR Development.
- Medical analysis of images.
- Detection/identification/evasion of the machine/vehicle.
Revenues from software, hardware and computer vision services will grow from $1.1m in 2016 to $26.2bn by 2025.
One of the main factors of the rapid development of computer vision is the widespread use of mobile phones with built-in cameras. Cloud technologies and various sensors gave impetus to the development of computer vision technologies and analytical tools. The current innovations are changing the retail trade.
Amazon Go deployed a combination of sensors, computer vision and deep machine learning in its stores. Due to the above-mentioned technologies, Amazon Go can determine what products buyers take from store shelves and allow them to leave the store without the formal registration of purchase.
BingoBox installed 200 automated shops in China. The company is planning to expand its business by entering the markets of Hong Kong and East Asia. In addition to product recognition, BingoBox has also implemented a technology that recognizes the faces of customers. Customers can pay for purchase with a fingerprint in the WeChat Pay or Alipay applications.
7-Eleven opened its signature self-service store in Seoul, which allows customers to make payments without cash or credit cards. The trading networks of Japan and 7-Eleven agreed to launch four stores without sellers, using tags instead of barcodes for identification of goods. With the use of RFID tags, the cost of all products in the basket can be calculated without purchasing these products. New tags on products will make life easier for buyers, manufacturers, suppliers and logistics companies. Real time tags will allow the demand for goods and information about the quantity of items in warehouses, on the road, and so on to be tracked. This concept is much closer to mass implementation than Amazon Go, and it is worth acknowledging that purchases will take much less time.
Similar stores continue to open, for example, Wheelys or Standard Cognition. There are also new tools for increasing sales: smart fitting rooms and mirrors, smart carts and baskets, facial recognition algorithms, etc. Giants such as Intel and IBM are investing in improving retail processes and optimizing supply chains.
Maersk explores ways to automate workflow and develop more efficient and transparent cargo management. In collaboration with IBM and Nestle, Maersk is developing its own blockchain technology based on the Hyperledger Fabric system, which enables the monitoring of millions of container shipments per year with better integration with customs services.
Walmart uses Hyperledger Fabric in a project aimed at tracking the origin, transportation and storage of mango and pork from China.
Yojee is a platform that provides the ability to manage supply chains in logistics with the use of artificial intelligence and blockchain. It replaces the dispatcher, monitors the status of orders in real time, generates accounts, manages tasks, etc.
4.2 Competitive analysis
Currently, there are quite a few projects that specialize in video analytics, machine learning and AI. Each of these projects is unique. These projects offer ready-made solutions, or write personal software for companies. Let us consider several such companies:
Hoxton Analytics uses cameras to determine the characteristics of consumers. Sensors and cameras are placed at ground level, so that the captured information does not violate people's privacy.
Walkbase analyzes the behavior of customers in the store, measures and optimizes the profitability of marketing campaigns and attracts customers to personalized marketing in the store.
Texel is a software developer and manufacturer of professional 3D scanners for 3D models of people and large objects. According to the developers, they created a 3D-cabin capable of scanning 40 objects per hour.
Bossa Nova Robotics is a service for retailers. The collection and analysis of product data on the shelf is automated with the help of robots.
Trax helps stores to collect data with photos of the shelf. Photos of products on the shelves are analyzed by AI, which recognizes each product, counts the number of SKUs for each category and applies machine learning (ML) to make clues.
OCSICO analyzes the activities of employees, tracks customer movements, queues, merchandising and offers various solutions for optimizing business processes.
Discovery allows brands to view data on stocks and sales in real time. Its Pre-Sale stage starts in June 2018.
Nucleus Vision IoT aims to provide easy-to-use technology for retailers, not relying on Wi-Fi, Bluetooth or facial recognition. It is built on its own sensory technologies, in-depth training and blockchain. Their sensors are already being tested in 10 stores. The ICO of Nucleus Vision IoT is being planned.
The OSA DC project is entering the emerging market of complete supply chain tracking and product control. Blockchain technology, subject to the openness of suppliers, sellers and distributors will get any information about the product in seconds. In the next few years, AI, ML and video analytics will be able to change logistics, sales, marketing and purchasing, but it is worth acknowledging that most specialists still use Excel, scanning and photographing.
The team registered two companies:
- Decentralized Limited registered in the British Virgin Islands.
- E.E.C. EXTRA ENTERTAINMENT CORPORATION LIMITED registered in Cyprus.
The OSA project is a partner of:
- ECR - ECR Lab will provide 3D layouts and product scanning, and transfer information to the OSA Master Data Catalog.
- Neuromation - The company specializes in image recognition.
- OSNOVA Capital - The company specializes in providing outsourcing services for accounting, tax, personnel and management accounting. It will provide AR for the OSA DC project.
- Paytomat - The company specializes in advisory and development.
- InspectorCloud - The company specializes in image recognition.
The OSA DC project is a member of the NRF retail association and it plans to become a sponsor of CGF, ECR supply chain and AI. The OSA project is planning to expand into the markets of the US, Japan, Korea, China, and the EU. The team is planning to develop the AI independently. According to the founders, there are more than 100 people and 14 advisors in the core team. The team plans to increase the staff by 65% by the end of 2019. Let us consider the key positions of the team:
Maximilian Musselius - Strategy and Vision Lead
- Moscow State University (2004 – 2008), specialist in Jurisprudence, Law.
- Lomonosov Moscow State University, Mater’s degree Management, Economics Faculty.
- Peoples’ Friendship University of Russia, Bachelor of Business Administration (BBA).
- 0paper, Electronic Documents (2010 – till present), Founder, Expert Council.
- ECR Europe (2010 – till present), Member of the Board of Directors.
- ECR Russia (2004 – till present), Executive Director.
Alex Zdrilko - Co-Founder, Business Development Lead
Alex has experience in various sales positions from his time at Japan Tobacco International (2010-2017). He has been involved in OSA DC since 2018.
- Ukrainian National University of Food Industry, master’s degree, Economy and Enterprise (2002-2007).
Alex Isaiev - Co-Founder, Business Development Lead
Alex Isaiev has previously worked as a Trade Management Manager at Japan Tobacco International. He also currently works with Retail Big Data solutions based on AI and blockchain in the Mania project. He has been involved in OSA DC since 2017 and in OSA HP since 2015.
- Mania. World of Business Simulations (2017 – till present), Mentor, advisor and investor in AI, Business Simulations and blockchain technologies.
- Mania. World of Business Simulations & Digital Transformation initiatives (2017 – till present), Executive Director.
Ruslan Pyshnyi - Co-Founder, Strategy & Marketing Lead
Ruslan has experience in major companies such as Japan Tobacco International and Russian Standard Vodka in key positions in marketing. He has been involved in OSA DC since 2018.
- International Institute for Management Development (2006–2007), High Performance Leadership Program.
- Kyiv National Taras Shevchenko University, (1989 –1995), Linguistics.
Arūnas Roličius - COO
Arūnas has experience in IT, finance and marketing. She specializes in analytics and strategic planning.
- Vilnius University (2004 – 2008), bachelor’s degree, International Business.
Esther Katz - VP Communications
Esther has experience in key positions in marketing and PR. He has been involved in OSA DC since 2018.
- Neuromation (2016 – till present), Strategic communications and digital marketing for AI, blockchain and SaaS.
- Kiev State Linguistics University (1992 – 1997), specialization: Linguistics, Communications.
Max Prasolov - Independent Director
Maxim states that he has released more than 50 animated commercials and 3D films and has experience working in international trade and with industrial brands. He co-founded the Ukrainian Animation Association in 2017.
- Neuromation (2016 – till present), CEO, President of Digital Economy.
- Nebeskey (2014 – till present), CEO.
- State University of Management (1994 – 1999), master’s degree, Market Development.
There are also specialists in marketing, product creation, lawyer and HR in the core team. Basically, the team has been working together since 2018. Consultants on business development in Asia (Japan, Korea) and blockchain development were also noted on the project website, but we did not see any confirmation of cooperation on their LinkedIn pages.
The development team has been working together for more than two years, first on the OSA HP project, then at OSA DC.
Roman Korolev - CTO
Roman has experience of working as a Python developer in Mail.Ru Group.
Oleksii Potapenko - Data Science Lead
Oleksii specializes in Machine Learning, Python, R, SQL, Statistics, Analysis, Data Mining, Passed Level I of the CFA Program.
Evgeny Tukhvatullin - Data Science Value Creator
Evgeniy specializes in business analysis, project management, process planning and automation.
Andrey Frolov - IT Developer, Blockchain Developer
The advisory board of the project includes specialists in blockchain, business development and machine training and lawyers, but none of the specialists confirmed their participation in the OSA project on their LinkedIn profiles. The extensive experience of the team members and advisors on the side of FMCG and retail manufacturers should be noted. The project team aims to use outsourcing solutions such as product scanning, image recognition, AI and IR.
The project development is conducted in Open Source mode on GitHub. At the time of writing the review, the code of the OSA token was still under construction.
Initially, a temporary ERC20 standard Ethereum blockchain OSA token will be used for purchases and use on the platform. After launching and transitioning the platform to a proprietary blockchain (using the Proof of Stake algorithm), all tokens will be exchanged to the OSA Coin of the proprietary blockchain in an equal ratio. According to the information provided, the new blockchain is planned to use the fork of one of the existing solutions - Nem, EOS or Cardano.
Token name – OSA Token
Symbol – OSA
OSA is a utility token which will be used within the framework of the platform for the following purposes:
- As a means of mutual settlement when concluding contracts between participants in the supply chain.
- Remuneration for OSA masternode blockchain operators.
- Remuneration for buyers for providing data on purchases, reviews of products, photos of store shelves when using the platform application and for other information provided by users that will improve the quality of the services provided.
- Commission fees on the platform.
- As a means of payment for various B2C services.
- Subscription to special offers.
- For the purchase of goods in shops integrated into the platform.
- Remuneration for retail chains for compliance with KPI standards, which are set for them by the supplier at the conclusion of the contract.
The following currencies are accepted during the Token Sale: ETH, BTC, LTC, ETC, BCH. We were given addresses of the wallets in which funds are received:
According to information provided by the founders, funds were raised in USD through a combination of winning d10e Seoul, a private investment of $0.5m, Angel investments of $0.45m, and the founders themselves contributed $4.2m for the development and deployment of the platform.
The OSA token (later OSA Coin) is the domestic currency of the platform. OSA DC is not geographically limited, as currently the OSA Hybrid Platform uses more than 20 RTLs and manufacturers in three countries worldwide. The OSA token can be a profitable and reliable means of mutual settlement for all participants of the ecosystem.
Analysis of factors affecting the future value of the token
The future dynamics of the exchange value of the OSA token will be determined mainly by two factors - the use of tokens on the platform and the management of token liquidity on crypto exchanges.
Taking into account that over 75% of the tokens, according to their distribution structure, will be blocked for 12 months after the completion of the ICO, the change in the token market price at this time will entirely depend on the volume of demand for the services provided by the platform.
Subsequently, the founders expect a gradual unlocking of tokens during the next 10 years for the team members and 10 months for token holders who purchased tokens during the token sale. Therefore, the future token exchange rate dynamics will depend on the actions of the team, the main task of which will be to control the volume of tokens on offer in the market.
Based on the information available, we think that during the first year (short-term) of the project, the price of the OSA token may increase if there is an increase in the number of users and favorable conditions both in the crypto market and retail business.
Analysis of investment risks
We note the following risks for the OSA DC project:
Only 23% of OSA tokens will be placed on the ICO. Therefore, 77% of OSA tokens will be reserved for various partners and teams. This distribution structure is basically a hidden additional emission which is 3 times bigger than the size of the primary placement which may cause a “blurring” effect on any positive impact on the exchange value of the OSA token. We note this risk as the main one to the medium and long-term plans of the project.
According to the information provided by the founders, more than 77% of OSA tokens blocked after the ICO will gradually go into free circulation within the next 10 years (10 years for the team and 10 months for the token holders who purchased them during the token sale). Obviously, all additional placements of OSA tokens should be made in times of success from the point of view of market conditions. It remains unclear how the crypto market will function in the long-term and whether the founders will have the opportunity to implement the conceived plans without jeopardizing the exchange value of the OSA token in a few years.
According to the information provided on the project website, funds received during the ICO will be stored in a diversified portfolio of ETH, BTC, LTC, BCH and ETC which, against the background of high volatility, keeps the exchange rate risk of such a portfolio at a sufficiently high level regardless of the share of ETH, BTC, LTC, BCH and ETC in it.
We also note that the OSA DC team is too dependent on the other projects and partners it is going to cooperate with in the first years of platform operation. We would like to highlight Neuromation in particular, which specializes in image recognition. Such dependence may result in circumstances, beyond the control of the OSA DC team, that could delay the launch of the finished and fully functional product, which in turn will lead to operational problems for the entire project in the first year, when OSA tokens are more likely to increase their exchange value according to the distribution structure and unlocking schedule.
We have not identified any other significant risks that could negatively affect the attractiveness of the OSA DC project.