Fetch is a digital economy based company that has developed what they consider to be, “The world’s first truly smart ledger”. This would harness the power of AI as being central to the project and creating an ecosystem which is consistently and automatically evolving thanks to machine learning. Ultimately, the Fetch ecosystem wants to create a situation whereby businesses and individuals can rely on the ledger to not only automate their business processes to become more efficient and profitable, but also to autonomously develop and act upon new solutions and opportunities as they emerge in any given space.

Open Economic Framework

This framework is where the Fetch ecosystem can exist, harmonizing both real-time and automated data to communicate and interact together. This framework is in effect the setting for learning and development of the project’s AI and machine learning capabilities.

Autonomous Economic Agents

These “Agents” are active, and facilitated within the Open Economic Framework, and act as vehicles for decision making within the ecosystem. These agents will interact in a flexible manner with each other to provide the most valuable economic solutions possible to monetize data and meet the needs of users as they arise. These agents are essentially AI powered dealmakers that will also continue to evolve to changing market conditions through machine learning.

Token

The Fetch ERC20 token (FET) will act as a key component within all operational features of the network. There is set to be a total of 1,152,997,575 tokens released over time.

The native token will effectively power all activities within the ecosystem. This includes network participation as well as development of nodes and economic agent development within the framework.

During the initial token sale, 20% of tokens will be distributed, with a further 20% held aside for future distribution. The rest of the tokens will be allocated as follows:

  • Company Founders: 20%
  • Project Foundation to support future developments: 20%
  • Advisors: 10%
  • Mining: 10%

Vesting periods for these tokens will vary from between 3 months for private sale purchases, up to 3 years in the cases of founders and foundation tokens.

The project will exchange ERC20 FET tokens for native FET tokens once they have launched their own mainnet, which is scheduled for mid-2019.

Team

Humayun Sheikh (Co-Founder/CEO)

He was Chairman of the Mettalis Group, a UK commodity trading company which he helped to grow into a multimillion-pound business during a 5 year tenure as well as being an early investor in DeepMind. Humayun then went on to found Itzme and uVue, before taking on his current role at Fetch.AI.

Toby Simpson (Co-Founder/CTO)

Simpson was one of the original developers with DeepMind prior to their takeover by Google. He since went on to join Ososim as CTO and has an extensive background in software development and over a decade’s experience as a CTO.

Thomas Hain (Co-Founder/CSO)

Hain is a Cambridge University graduate where he went on to lecture prior to his tenure as a professor and department head with the University of Sheffield where he has been working for over 14 years.

Advisors

The Fetch.AI project only features two advisors. Namely these are Melvyn Weeks, an economics advisor of the project who is a Cambridge University Lecturer, and Monique Gangloff as a biotech advisor. She is also a senior scientist at the University of Cambridge.

Partners

The project has several well-recognized partnerships. These include Warwick Business School, Token Market, ULedger, Mobi, and Outlier Ventures.

Verdict

Below is a breakdown of the risks and growth potential of Fetch.AI.

Risks

  • The project is still in the very early stages of development with roadmap details which are not hugely extensive. (-2)
  • Many token metrics are quite unclear. This specifically includes no availability of exact pricing during the crowdsale. (-2)
  • There appears to be a small percentage of tokens made available to the public, whilst a large percentage is allocated toward project-oriented areas (Founders, Foundation, and Advisors total 50%) (-1)

Growth Potential

  • The project possesses a large and highly experienced team from a variety of academic, practical, and corporate backgrounds. (+4)
  • The technical proposals and concept of the project are very attractive and presented in a professional manner. (+2.5)
  • The target sector of the project is one which can ultimately benefit very much from the success of Fetch AI in automating and enhancing the blockchain through AI and machine learning. (+2)
  • AEAs operating within the open framework allow the project to overcome scalability issues better than other ecosystems. (+2.5)

Disposition

Fetch AI is a project which is proposing a very exciting and necessary solution to the issue of current ledgers. This is something which can also greatly benefit users. The implementation of AI and the use of AEAs can help propel the project to the forefront of the industry and be a great success. It is also backed by a very strong team of academics from the likes of Cambridge as well as pioneers in the AI field, such as CEO Sheikh and CTO Simpson (early investor in and one of the original developers at DeepMind respectively).

The future of the project looks positive, however the company has to continue being active in producing practical and quantifiable progress on technical development. This is yet to be very evident in practice.

If the platform succeeds through testing, it has great potential.

Overall Project Score: 6/10

Investment Details

  • Type: ERC20 then Native
  • Symbol: FET
  • Platform: Ethereum prior to Mainnet (2019 Q2)
  • Crowdsale: September 30th – November 30th
  • Minimum Investment: Unspecified
  • Price: Unspecified ($0.13 approximately, deduced from total token release/hardcap)
  • Hard Cap: $30,000,000
  • Payments Accepted: ETH
  • Restricted from Participating: Afghanistan, Belarus, Burundi, Central African Republic, China, Congo, Ethiopia, Guinea, Guinea-Bissau, Iran, Iraq, Lebanon, Libya, North Korea, Serbia, Somalia, South Sudan, Sri Lanka, Sudan, Syria, Thailand, Trinidad and Tobago, Tunisia, Uganda, Ukraine, United States of America, Venezuela, Yemen, Zimbabwe

Featured image courtesy of Shutterstock. 

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