
Cambridge, England
2017
AI Agents, Enterprise Software, Blockchain, Decentralized Computing, Financial Services, E-commerce, Logistics, Transportation, Software Development
Fetch.ai is an artificial intelligence company developing autonomous AI agents and decentralized infrastructure that allows software agents to discover services, communicate, and perform tasks on behalf of users and businesses. Its technology combines agentic AI, machine learning, blockchain, and distributed software systems.
The company provides tools for building, deploying, and connecting AI agents through an open ecosystem. Its platforms include Agentverse, an AI agent marketplace, and ASI:One, a personal AI assistant designed to interact with specialized agents and coordinate activities across different digital services.
Fetch.ai develops software infrastructure that enables autonomous AI agents to perform tasks, exchange information, and interact with other agents without requiring users to manually operate multiple applications.
Developers can build agents that connect to APIs, databases, and external services, then register them on Agentverse, where users and other AI systems can discover their capabilities.
Through ASI:One, individuals can describe what they need using natural language. The platform identifies relevant agents and connects them to complete supported activities, such as finding services, retrieving information, or coordinating bookings.
Fetch.ai also provides business-facing AI agents that organizations can use to make their products and services accessible through conversational interfaces.
Its infrastructure supports agent communication, decentralized registration, and blockchain-based transactions, allowing independent AI systems to collaborate across a shared network.
Fetch.ai combines multi-agent systems, large language models, and decentralized computing to create infrastructure for autonomous software agents.
Its uAgents framework is a Python-based development toolkit for building agents that can exchange messages, access external services, and coordinate tasks. Developers can define agent behavior, communication protocols, and event-driven processes without creating a separate communication system for every application.
The company’s Agentverse platform provides an environment for registering, hosting, managing, and discovering agents. Agents built with uAgents or compatible frameworks can be published to the marketplace and made accessible to users and other AI applications.
Fetch.ai also develops ASI:One, a large language model designed for agent-based interactions. It interprets natural language requests, identifies relevant agents through Agentverse, and routes instructions to agents capable of performing specific tasks.
The ecosystem incorporates blockchain technology through the ASI Network. Its Almanac smart contract maintains a registry of agents, supporting decentralized discovery and communication. Blockchain components also provide infrastructure for transactions and digital asset management.
Fetch.ai supports agent-to-agent communication and multi-agent collaboration, allowing specialized agents to exchange information and coordinate actions. This enables applications where several independent software agents contribute to a larger task.
Together, these technologies provide a framework for connecting AI reasoning with external tools, digital services, and automated transactions.
Most conventional AI assistants primarily respond to questions or generate content. Fetch.ai focuses on extending these capabilities through autonomous agents that can interact with services and perform tasks.
Its technology addresses an important challenge in agentic AI: enabling independently developed agents to discover one another, exchange information, and collaborate across different applications.
The combination of AI models, agent marketplaces, and decentralized infrastructure introduces an alternative to systems where all tools and services must operate within a single software provider’s environment.
Fetch.ai is also relevant to the development of an agent-based digital economy, where AI agents can represent individuals or businesses, negotiate access to services, and participate in supported transactions.
As AI applications become more capable of executing multi-step activities, Fetch.ai illustrates how software infrastructure is evolving to support interactions between autonomous AI systems rather than only between people and applications.
ASI:One is a personal AI assistant built for agent-based interactions. It uses a large language model to understand user requests, identify specialized agents, and coordinate tasks across connected services.
The platform supports personalized conversations, persistent memory, and interactions between multiple AI agents. Users can access it through web and mobile interfaces.
Agentverse is an AI agent marketplace and development platform where developers can register, deploy, manage, and discover autonomous agents.
It provides agent hosting, testing tools, and a searchable directory of available agents. Registered agents can be accessed through ASI:One and can communicate with other compatible agents.
uAgents is an open-source Python framework for building autonomous AI agents. It provides tools for agent communication, message handling, event-driven execution, and integration with external services.
Developers can use uAgents to build individual agents or multi-agent systems that coordinate activities across different applications.
Fetch Business provides tools for organizations to create AI agents representing their products, services, and business operations.
Businesses can establish agent profiles, connect service information, and make their agents discoverable through Agentverse. These agents can respond to customer requests and interact with other agents through supported integrations.
Fetch.ai’s technology supports applications where AI agents need to access information, coordinate services, or complete tasks across different systems.
In e-commerce and retail, businesses can create agents that help customers discover products, compare available options, and interact with purchasing services.
For travel and transportation, agents can coordinate searches, compare services, and assist with reservations through supported providers.
In financial services, developers can build agents that retrieve financial information, analyze data, and automate selected workflows.
For logistics and supply chain management, multi-agent systems can coordinate information between transportation services, inventory systems, and operational platforms.
Fetch.ai also supports software development and enterprise automation through agents that connect APIs, databases, and business applications. Its open architecture allows developers to build applications for additional industries without requiring every agent to use the same underlying AI model.
Fetch.ai develops the broader infrastructure for autonomous AI agents, including development tools, discovery services, and decentralized networking. ASI:One is its user-facing AI assistant that interprets requests and connects users with specialized agents through the Fetch.ai ecosystem.
Agentverse allows developers to publish, host, test, and manage AI agents. It also provides a marketplace where agents can be discovered by users and other AI systems. Agents registered on Agentverse can be integrated with ASI:One for conversational access.
No. Developers can create agents using Python and the uAgents framework without directly implementing blockchain functionality. Blockchain components become relevant when applications require decentralized registration, wallets, or network transactions.
The Artificial Superintelligence Alliance, also called the ASI Alliance, is a collaboration involving Fetch.ai and other decentralized AI projects, including SingularityNET. It brings together technologies for AI models, autonomous agents, decentralized computing, and related infrastructure.
Yes. Fetch.ai supports integrations that allow agents developed with compatible external frameworks to participate in its ecosystem. Developers can connect agents using supported communication protocols and adapters, including integrations involving CrewAI and Model Context Protocol tools.
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