1. Background of the Fetch AI project

Fetch AI is a decentralized artificial intelligence (AI & Blockchain) project founded by Humayun Sheikh (CEO) and his team, which began the research and development of basic technology as early as 2017. Its core architecture integrates Agents, Agentverse, AI Engine, and Fetch network, creating a highly autonomous digital economy for individuals, enterprises, and devices.

According to public information, the Artificial Superintelligence Alliance (hereinafter referred to as: FET) was first issued on 2019-02-24, and later listed for trading on the Gate platform, allowing more investors and developers to directly access and use FET. The project hopes to promote artificial intelligence in supply chain management, automated trading, the Internet of Things, and a wide range of future autonomous systems to achieve higher efficiency and lower costs, realizing a highly automated, trusted digital ecosystem.

Source:Fetch AI Official Website

2. The technical principles of Fetch AI

The core concept of 2.1 Agents

In Fetch AI’s theoretical system, ‘Agents’ are the most core technological form. The so-called Agent is an intelligent program entity with autonomous decision-making and communication capabilities, capable of independently or collaboratively executing specific tasks in a blockchain environment.

• Autonomy: Agents can make independent decisions based on preset strategies and artificial intelligence algorithms without excessive human intervention.
• Discover and collaborate: all Agents registered in the network’s smart contracts (such as Almanac) can be searched, invoked, and organized into collaborative networks.
• Decentralization: Multiple Agents work on top of distributed infrastructure, reducing reliance on centralized servers and improving fault tolerance and security.

2.2 AI Engine and Intelligent Routing

AI Engine is an engine used to understand natural language commands and convert them into executable tasks.

• Natural Language Parsing: Analyzing user input through various large-scale language models (LLMs) and machine learning models.
• Dynamic routing: In the list of functions registered by Agents in the network, automatically search and assign the most suitable Agent to fulfill user needs.
• Multi-agent collaboration: If a single Agent is difficult to complete independently, the AI Engine will decompose the task and organize multiple Agents to collaborate on processing.

2.3 Agentverse: Integrated Agents Management and Deployment Platform

Agentverse is an official SaaS platform developed by Gate, providing developers and enterprises with easy multi-agent hosting, management, and monitoring.

• Web IDE: Create, test, and iterate Agents in the cloud to shorten deployment cycles.
• Mailbox function: Allows agents to receive messages while offline, automatically synchronizes after reconnecting, reducing resource consumption.
• Registration and Visualization: Agentverse and Almanac contract integration allows newly deployed Agents to be registered on the network, enabling other Agents or AI Engine to quickly discover and invoke.

2.4 Fetch Network: A high-performance chain based on Cosmos SDK

Fetch AI’s underlying network is based on the Cosmos SDK, using the Tendermint consensus algorithm:

• Scalability: Cosmos’s modular design empowers the Fetch AI network with high concurrency and plug-and-play capabilities.
• Almanac contract: responsible for recording the registration information of all Agents, while ensuring data transparency and immutability.
• FET Coin: Used for paying network transaction fees, staking, and governance voting functions.

Source:Fetch AI Architecture|Whitepaper

3. FET Coin Introduction and Market Performance Overview

3.1 Introduction of FET Coin

According to the official project description, FET (Artificial Superintelligence Alliance) advocates combining machine learning (ML), artificial intelligence (AI), multi-agent systems (MAS), and decentralized ledger technology to build an Economic Internet.

• Autonomous system empowerment: FET is committed to enabling more business scenarios to achieve automation and autonomy.
• Multiple applications: from data processing, hardware collaboration, to personnel, infrastructure management, can all be executed and optimized by the intelligent body of the FET ecosystem.
• Reduce human resource consumption: The autonomy of the traditional market often requires a large amount of manpower and resources, but through multi-agent collaboration, more efficient and smooth transaction and data exchange processes can be achieved in various markets or industries.

FET Coin primarily serves as the “fuel” needed for network transaction fees and secure communication in the network. Nodes and Agents also need to stake FET to participate in specific network operations, which is a crucial means to ensure network security.

3.2 FET Coin Market Performance Overview

The following data is from Gate platform（FET/USDT trading link）（As of 20250303）

The current price of FET is about $0.6783, with a 24-hour increase of +5.79%, a 24-hour high of $0.7768, and a low of $0.6405. It is currently ranked No.62, with a market cap of approximately $1.77B and a circulating supply of 2.60B FET.

It is worth noting that the all-time high price of FET is $3.45 (2024-03-28), and the all-time low price is $0.008169 (2020-03-12). Since its issuance, the price of FET has experienced significant fluctuations, reflecting the overall changes in the cryptocurrency market during this period and the fluctuations in interest in AI track projects.

Source:Gate.io Spot Trading Zone

4. FET Coin Token Economy Model

The native cryptocurrency of the Fetch AI project is FET Coin, which mainly has the following economic properties and functions:

1. Payment and transaction fees: When data transactions or network operations are conducted between multiple intelligent agents, FET needs to be paid as fuel fees;
2. Node Staking: Network validators can provide node services by staking FET, earning block rewards, and participating in project governance;
3. Governance Voting: FET holders can vote on proposals such as network upgrades and parameter adjustments.
4. Security mechanism: To prevent malicious nodes or Agents, some key operations (such as contract deployment, Agent registration) require a certain amount of FET to be staked.

4.1 Circulation and Inflation Mechanism

• Initial distribution: FET was officially released on 2019-02-24, with a total supply of 2.71B FET (i.e. Max Supply).
• Circulating Supply: The current Circulating Supply is approximately 2.60B FET.
• Inflation and Destruction: Some FET will be used for ecological incentives or node rewards, while the network may also destroy or repurchase in specific circumstances to maintain the token economic balance (specifically depending on project governance proposals and on-chain data).

4.2 Market Cap and Valuation

• Market Cap: According to the data from Gate.io, FET currently has a market cap of about $1.77B, placing it in the medium to upper range in the crypto market.
• Fully Diluted Market Cap: When all 2.71B FET are in circulation, the FDMC is approximately $1.85B, with a market cap/FDMC ratio of 95.96%, indicating that most of the tokens are already in circulation in the market.
• Market sentiment impact: Due to the high attention on the concept of AI+ blockchain, the market value of FET may continue to be influenced to a certain extent by the success or failure of related projects.

5. Fetch AI technology stack and product ecosystem

To help developers, businesses, and communities better build multi-agent applications, Fetch AI provides a range of tools and platforms:

5.1 uAgents Framework

• Lightweight Development: uAgents provides basic communication protocols, message processing, and convenient interfaces for integrating AI/ML for multiple intelligent agents.
• Python ecosystem: Most examples and encapsulations are based on the Python language, which can be quickly mastered.
• Use cases: supply chain optimization, quantitative trading bots, IoT device linkage, etc.

5.2 Agentverse Platform

• Cloud IDE: write and test multi-agent code online, and deploy to the testnet or mainnet at any time.
• Template support: Officially pre-built Agent templates for common business logic, developers can directly modify parameters to accelerate implementation.
• Mailbox: Offline message receiving function, solving the resource consumption caused by the agent being online all the time.

5.3 DeltaV Chat Interface

• Natural Language Driven: Users or developers issue requests to the system through DeltaV’s chat interface, and the AI Engine automatically parses and invokes the correct Agent functionality.
• Visual Task: Easy to view the execution progress and issue multi-round instructions in the dialogue interface.
• Multi-model compatibility: The official plan is to make DeltaV and AI Engine support more LLM (Large Language Model) to expand the availability of Agent.

5.4 Fetch network and main components

• Almanac contract: records the basic information and status of Agents, forming a unified registry for multi-Agent collaboration.
• Fetch Name Service (FNS): Provides a user-friendly naming system for easy recall and retrieval of Agents.
• Fetch Ledger: Based on Cosmos SDK, high-performance and secure, supporting smart contracts and multi-agent interaction;
• FET Coin: used for transaction fees, staking, and governance throughout the entire network.

Source:Fetch AI Infrastructure

Summary

Since its launch in 2017, Fetch AI Coin (FET) has been exploring feasible paths to deeply integrate multi-agent systems with blockchain. Its technological core lies in using a distributed Agents system to enhance the automation and efficiency of the digital economy; by collaborating components such as AI Engine and Agentverse platform, it provides developers and enterprise users with a relatively complete toolchain. Judging from its current (as of 2025-03-03) market value, circulation, and activity, FET occupies a certain position in the AI+Blockchain track, and shows potential growth space in areas such as supply chain, IoT, metaverse, and financial transactions.

However, investing in and using FET also requires constant attention to technological updates, application progress, market fluctuations, regulatory dynamics, and other factors. The concept of multi-agent systems is groundbreaking, but in the process of large-scale commercial implementation, it may still face security and performance challenges. It is crucial for both ordinary users and professional investors to have a deep understanding of Fetch AI’s ecosystem and its roadmap. In this rapidly iterating industry, as a representative of decentralized artificial intelligence projects, FET is expected to continue to contribute unique value to the future of the digital economy, but it also needs careful evaluation of various risks before making decisions.