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Faceter Rating Review

Stable+

Investment Rating

Expiry date : Expired 30 Jun 2018

Description of the services and scope of the Project

The Faceter platform offers the following features:

  • Intelligent video surveillance enabling:
    • Advanced facial recognition including partially hidden faces.
    • Recognition of sex, age, race.
    • Recognition of features of the human body such as height, weight and physique.
    • Recognition of emotions.
    • Identification of pets.
    • Analysis of video streams from real-time surveillance cameras for detection and recognition of objects and events.
    • Training of neural networks for assessing cameras in the field of view and responding to various situations (for example, fire detection and calling firefighters).
  • The B2C for households sector will enable:
    • Parents to be notified that their child has left school.
    • Detection of intruders.
    • Integration with smart home technology.
  • The B2B sector for enterprises will offer opportunities to expand security functionality:
    • Automation of checkpoints and identification of intruders.
    • Tracking worker arrival and departure.
    • Recognizing and counting numbers of visitors and keeping security logs.
  • The B2G Sector for Government Organizations will provide the following opportunities:
    • Analysis of video streams on streets, roads, railway stations, airports, etc.
    • Recognition and classification of cars as well as their license plates.
    • Ability to integrate with databases.
    • Facial recognition with database or archive search will enable finding missing people, criminals, etc.
  • High-precision face recognition technology will enable tracking each individual and generating reports about where and when this person was filmed.

Facial recognition includes 6 stages:

  1. Receiving and decoding video streams from cameras.
  2. Face detection (in case a camera is not equipped with built-in face detection technology).
  3. Face alignment and framing for better recognition.
  4. Obtaining a vector of characteristics for each person using deep convolutional neural networks.
  5. Vector clustering, comparison of feature vectors with available databases and their placement in the storage system.
  6. Output of results through API.

The process is clearly illustrated below:

Video stream processing will be performed using ready-made solutions such as SONM and Golem, as well as Faceter Fog, the project’s own decentralized computer network built on miners’ equipment.

Each miner will be a node in a distributed network, and quality assessments will be performed using a smart contract that implements the "Proof-of-Recognition" concept by comparing a hash of the computed calculations of all nodes. In the event that the hash is different, this will indicate a shortcoming and the miner will therefore not receive a reward.

The distribution of tasks and verification between nodes will be implemented by special node orchestrators (Video Hubs) which are video concentrators and confidential data obfuscators.

Obfuscation (depersonalization) of data is designed to preserve the privacy of those whose cameras are connected to the platform.

It should be noted that the platform has a ready-made product for business customers and an MVP for consumers [https://app.faceter.io/auth/signup].

The features are aimed at providing high-quality, affordable services for customers of all kinds, from individuals to large corporations. In our opinion, Faceter’s product could be popular in various industries.

Market review

Market analysis

The video surveillance market has experienced a continuing growth trend in the last decade. Using video cameras for security is no longer exclusively the domain of large enterprises, banks, airports and busy city areas. Video surveillance is actively used in various industries - transport, shops, offices, etc. Due to lower prices for video surveillance technology, the equipment required is now accessible to the private sector.

According to Statista research, in the period from 2009 to 2014 the global video surveillance market showed active growth from $17.1 bln in 2009 to $30.7 bln in 2014. The forecast value for 2019 will be about $52.6 bln – more than three times greater than a decade ago:

Growth in the video surveillance market is also confirmed by Markets & Markets research. According to the report, this market segment was estimated at $30.37 bln in 2016, and the forecast for 2022 is about $75.64 bln, with CAGR of 15.4% between 2017 and 2022.

Active growth is also evident in other segments related to the video surveillance market. According to a Zion Market Research report, an increase in the number of terrorist acts and the frequency and intensity of security breaches have become key factors for

the rapid growth of the global video analytics market. Its volume was estimated at $1.89 bln in 2016. According to this forecast, growth to $11.10 bln is expected by 2022, and the CAGR of this market segment will be 34.3% between 2017 and 2022:

Competitors analysis

The video surveillance sector has a large number of non-blockchain CCTV companies such as:

Ivideon – A cloud service that provides video surveillance solutions for home and business.

Currently, the main advantages of this platform are:

  • 5 years operating in the market.
  • 2m users in more than 100 countries.
  • 15 datacenters worldwide.
  • It is multi-platform.

In addition to video surveillance, the platform offers hardware with integrated proprietal software.

Vocord – Focused mainly on the business sector, this company was founded in 1999. Provides the following products:

  • Recognition of people including gender and age.
  • Recognition of vehicle license plates, control of entry/exit of vehicles and video recording of violations of parking rules.
  • Video surveillance, as well as cameras for video analytics and face recognition.
  • Recording audio streams (telephone conversations, monitoring and recording of IP telephony).

There are also other solutions that use AI for video analytics, as well as face and object recognition, for example IntelliVision or the Cherry Home platform (launched in June 2018) which uses AI, computer vision and biometrics to provide security in homes; it is also able to learn to recognize threatening situations and respond to them.

Faceter has the following advantages over competitors:

  • The platform is aimed at providing video surveillance and analysis services accessible to consumers.
  • Intelligent video surveillance - machine learning will enable software to recognize and analyze video streams in real time and to respond to events occurring (for example, to recognize a fire and call firefighters).
  • There is a market-ready product for business.
  • The project team has already had a successful launch for a product in the field of computer vision (Pay.Cards).
  • Facial recognition technology that enables tracking anyone, as well as providomg information about where and when this individual was photographed by cameras.

We think that the combination of current growth in the video surveillance market and the advantages listed above will allow the project to occupy its niche in the market.

Team and stakeholders

There is a team of nine people engaged in the development and creation of the project, along with three advisors.

Key positions are occupied as follows:

 

Founders:

Robert Pothier, CEO and Co-founder.

Has extensive experience working for large companies (Pinnacle Micro, Wallet One). Has developed and implemented projects for electronic wallets, gambling and KYC, as well as banking solutions in the UK, Spain, Italy and a number of African countries.

Work experience:

  • Pinnacle (2008) Channel Accounts Manager.
  • Wallet One: General Manager (2009-2015), Co-Owner Mozambique (2016 - present), New Business Development and Operational Consultation Johannesburg (2016 - present).

Education: Damelin College (1999 – 2003), specialization - Marketing and Business Management.

 

Vladimir Tchernitski, Co-founder and CTO.

A professional with extensive experience in software development, neural networks, computer vision and biometrics. He has been the head of the R&D group in a software development company for outsourcing for several years.

Work experience:

  • Azoft - Software Developer (2008-2012);
  • Head of R&D department (2012-2015).

Education: Chita State Technical University (1994-1999), specialization in Power Engineering.

The team of founders looks strong; it has extensive management experience, business processes, software development with computer vision and biometrics, research in neural networks for visual information recognition, experience in IT companies and the implementation of electronic payment systems.

 

Team:

Paul Scott, Business Development.

Paul is an experienced professional in financial markets and emerging-market technologies with deep-level FinTech, InsurTech and Big Data ecosystem knowledge, including the use of advanced technologies (utilization of leading-edge technologies). He also consults ICO projects.

Education: University of KwaZulu-Natal (1991-1994), specialization - Finance, Economics.

Heriot-Watt University (2000-2002), specialization - Accounting, Marketing.

 

Leon Olckers, Technical Deployments

Leon has extensive experience in the field of CCTV. He has participated in projects on biometrics, access control, observation of goods and customer behavior at numerous sites.

Education: Hopefield (1984-1989), specialization - Photographer and media officer. Volunteer at Tygerberg Association for the physically disabled (2014 – present).

 

Jayson Gouws, Solutions and Distribution.

Jayson is a technical security specialist. He has experience in sales of video surveillance systems and large-scale security projects.

Education: WITS Business School (1998-1999), Business Management

 

Aleksandr Chernov, Tech Lead.

Work experience:

  • Bananamedia (2014-2016), Development Team Lead.
  • Wallet One (2016-2017), Systems Analyst.

Education: Orenburg State University (2008-2013), specialization - software development.

 

Vitaliy Kuzmenko, Mobile Development

Work experience:

  • Web developer (2009-2014) in companies such as WebRegul, LYUMI ART, DELTA Internet Agency, LightTrader;
  • Tasty (2015-2016), iOS Developer, Team Lead.
  • Wallet One (2015 -present), Mobile Team Lead, Senior iOS Developer. Education: College of Radio Electronics, Information and Industrial Technologies (2010 - 2013), specialization - software. IOS Development Course (2013-2014).

 

Advisors:

Igor Karavaev, Investor Relations.

Blockchain investor relations consultant. Worked as executive director of Skolkovo Foundation, an investment and business development specialist for corporations such as Rosatom, Sibur, Transmashholding.

Advises such projects as Sharpay, Priority Token, ZeroState, Skyfchain.

 

Ken Huang, Senior Academic Advisor.

Provides technical and strategic assistance to blockchain projects. Has experience at Huawei as director of cybersecurity.

Advises such projects as 0chain, familypoints, THEKEY, Waykichain, Sharpay, XCoinPay.

 

Wulf Kaal, Blockchain Expert.

Provides a variety of assistance to blockchain projects as well as large corporations and private foundations regarding various aspects of financial markets.

Advises such projects as Tokenbox, TokenStars, Moms Avenue, The Token Fund, Ankorus, ETHLend, Ties.DB, Storiqa, Vestarin, Mirocana, Semad Platform, advalorem.io, Tokia.

 

Partners:

Debonairs Pizza one of the first customers for Faceter, currently signing an agreement for permanent cooperation.

EPI-USE - the world’s largest independent purveyor of SAP country payroll software for regions in which SAP does not offer a standard payroll solution.

AXIS - This Swedish manufacturer of network cameras for the physical security and video surveillance industry is an application development partner.

In the course of studying the project’s activity online, we have not found anything negative; the project has a good reputation amongst those aware of it.

In summary, the project has gathered a strong team that has experience in management, video monitoring and research. The team has joint work experience in another project known as Pay.Cards. This product has been tested and partnership agreements have been concluded with large companies. The project is planning to expand its staff and improve various technical aspects. The team is one of its strengths, with many years of experience, an extensive customer base and a clear understanding of its market. A lack of detailed information on some members of the team is one weakness however.

Token analysis

At the time of writing, there is no open code for the token on GitHub yet. However, according to the founders, the token code will be posted soon, with an audit from Ambisafe. The documentation also states that tokens will be issued on the Ethereum blockchain in accordance with the ERC20 standard.

FACE tokens are used to pay for services inside the platform; hence, FACE is a utility Token. The prices for platform services will be set in USD; mechanisms will be implemented that enable users to pay using convenient methods (bank cards, electronic wallets and cryptocurrencies) with automatic conversion of deposited funds into FACE Tokens.

The client's smart contract will distribute the tokens as follows:

  • 60% is returned to the system’s reserve pool.
  • 20% is held by the platform.
  • Remaining tokens are burnt.

Users whose cameras are connected to the platform will be able to take part in finding people; if they succeed they receive a reward in tokens. Data from users’ cameras remain confidential.

When concluding a smart contract with a miner, tokens are retained from the system pool for subsequent payment for video stream processing.

Initially, the platform will use tokens on the Ethereum blockchain; subsequently there may be a transition to a proprietary blockchain complete with token migration. This will solve a problem of decentralized distribution of tasks, increase the system speed, ensure independence from the Ethereum blockchain and reduce transaction costs.

According to the information provided, the main areas of the project using blockchain are:

  • The issue of FACE tokens.
  • Building a decentralized infrastructure (fog computing).
  • Implementation of a "Proof-of-Recognition" mechanism.
  • Receiving client payments, assigning orders in smart contracts, and transferring payment to miners.

In our opinion, the role for the FACE token on the platform is logical and the token may come to be in demand, as payment for Faceter services in tokens is merited by speed, transparency and the ability to pay anywhere worldwide.

Analysis of factors affecting the future value of the token

The FACE token is an infrastructural element of the platform. According to the White Paper, all mutual settlements within the platform will occur using FACE tokens or other payment instruments (bank cards, electronic walletsm or cryptocurrency). To ensure normal functioning for FACE tokens, Faceter will implement mechanisms for instant payment conversion. Thus, with the increase in number of users, demand for FACE tokens will grow, which will lead to an increase in their value.

Up to 65% of project revenue will be directed to the purchase of tokens to replenish the reserve pool quarterly. The buyback price will be based on the market value of FACE Token, not below. The team provides two mechanisms for buyback of tokens:

  1. Based on an Ethereum smart contract, users will be able to hang orders for the purchase or sale of tokens in their personal account.
  2. On crypto exchanges where FACE Tokens are to be traded (HitBTC and a number of other smaller ones - Liqui, Tidex, Exmo).

There is also a mechanism for burning tokens. A smart contract distributes tokens automatically. A portion of tokens will be burned. As a result, the number of tokens in circulation will gradually decrease which, with stable or increasing demand will also push their price up.

A financial model describing the main revenues and expenditures for the project in the long term is not presented in the documentation. According to the founders, this model will be disclosed to interested investors upon request only after signing a non-disclosure agreement. In the course of writing this review, we were presented with a financial model and we can confirm its availability.

In view of the fact that the team is bringing its product to a dynamically developing market, the product will be in demand in many countries, and with the cost of the finished product already determined (about $10 per device), it can be assumed that the number of Faceter customers will grow in the B2C, B2B and B2G markets, which will increase demand for FACE Tokens.

In a scenario where all raised funds are utilised as planned, all declared functions will be implemented if the project collects its maximum amount of funding (hard cap).

According to the roadmap, launch of the platform is scheduled for the end of 2018 which means that a significant demand for FACE Tokens and a fundamental increase in their value should not be expected before this point.

There are two main factors that could influence the price of FACE in the short term. The first one is an extended PR campaign for promotion of the project’s benefits to a wide range of investors (currently, information on global marketing strategy is not disclosed). There is already much interest in the project. It is suggested to reserve tokens in a personal account in advance to take part in the token sale and receive an additional bonus of 10% to 20%. There is a possibility that token demand will not be satisfied during the main stage of the token sale; interested investors will then buy up FACE Tokens in the secondary market, pushing the price up.

It is worth noting that 15% of tokens given to the project team will be frozen by smart contract for 2 years, which means that the team is serious about its product; this will be an incentive for them to direct all their efforts to the development of the project at least during this period.

At the same time, it should be noted that in the course of preliminary sales, $10m tokens (9417.6 ETH) were sold with significant discounts (up to 50%) which may immediately serve as a deterrent to the growth of the token price, as some early investors may want to exit positions, fixing profits equal to the size of the bonus received.

Regarding the long-term prospects for the project, we think that FACE Tokens and the project as a whole have enough factors for growth and successful implementation.

Investment risk analysis

The rate for 1 FACE is tied to ETH during the token sale. Given the high volatility of cryptocurrency, this creates an additional risk for fiat investors, since in the case of an increase in ETH rates, the price of 1 token in fiat increases.

There is also an economic risk, as Faceter does not disclose financial indicators and forecasts. According to the founders, the fact that the public placement of the financial model can be recognized as "guaranteed" development plans, in the event of a deviation from the financial model it can be used against the project.

Faceter plans to attract both individuals and companies to the platform; there are also solutions aimed at government agencies. The use of tokens by legal entities and especially by state bodies can be difficult and sometimes impossible due to difficulties in regulating the crypto market in different countries.

The global marketing strategy has not been published; for this reason, the project is  also in the risk zone and current investors will not be able to obtain a clear idea about future product promotion.

 

 

The information contained in the document is for informational purposes only. The views expressed in this document are solely personal stance of the ICOrating Team, based on data from open access and information that developers provided to the team through Skype, email or other means of communication.

Our goal is to increase the transparency and reliability of the young ICO market and to minimize the risk of fraud.

We appreciate feedback with constructive comments, suggestions and ideas on how to make the analysis more comprehensive and informative.

Ratings

We assign the Faceter project a “Stable+” rating.

The Faceter project is entering the growing market for video surveillance and aims to solve a number of real-world problems. The project’s chance of solving these problems makes it promising and potentially in high demand.

Faceter has a strong team and advisors, who between them have extensive experience in this business area. The fact that the management has sufficient experience of joint work and is successfully developing its business is a definite plus for Faceter.

The company has developed a number of mechanisms to boost the investment attractiveness of the token; in particular a mechanism for token burning and buyback is provided.

Having studied the available information and written this review, we did not identify any significant risks that could negatively affect the price of the token. The fact that Faceter closed its pre-sale ahead of schedule having collected more than $10 million over a short period of time shows the level of interest this project is attracting.

However, we draw investors' attention to a lack of open access to some of the important components of a beginner project, including a long-term financial model and global marketing strategy. This prevents us assigning a higher rating.

General information about the Project and ICO

Faceter is a distributed computing platform based on mining for face recognition and the intelligent analysis of video streams from CCTV cameras using distributed computing capacity.

Faceter makes video surveillance smarter with the use of neural networks. These functions allow a CCTV system to understand a situation and respond to it, offering its customers a new level of security.

Smart contract platform: Ethereum blockchain

Contract type: ERC20

Token: FACE

Soft cap: $5,000,000

Hard cap: $40,000,000

 

Pre-Sale:

Start date: February 5th, 2018 End date: February 15th, 2018 Tokens to sell: 108,000,000 FACE

Bonus program: 50%, 40%, 30%, 20% determined by whitelist position. Extra 5% bonus for individual purchases greater than $10,000.

 

Token Sale:

Start date: February 15, 2018

End date: March 30, 2018

Tokens to sell: 300,000,000 FACE

Bonus program: 20% for early contributors only.

Price: 0.0872 ETH = 1000 FACE

Min purchase amount: no limitations

Max purchase amount: no limitations

Accepted currency: ETH, BTC, LTC, XRP, DASH, XEM, XMR, BCH

116,245,226 FACE ($10 mln) were sold as a result of the pre-sale and the soft cap has been achieved.

All unsold tokens will be burned after the token sale. The distribution of tokens is as follows:

There is no additional emission.

Funds raised during the token sale are planned to be allocated as follows:

  • R&D and Hardware Solutions - 43%
  • Outreach, Partnerships and Integration - 31%
  • SG&A- 21%
  • Legal Costs- 3%
  • Other - 2%