‘Fetch.ai’ – Transform your legacy systems to be AI ready without changing your existing APIs

Fetch.ai is a Cambridge-based company that aims to provide tooling for communication and actions between AI applications, using blockchain technology and decentralized machine learning.

It’s an open platform that lets you transform your legacy systems, make your services discoverable, and integrate with other developers and partners. A platform to connect multiple integrations to create new services.

Fetch.AI is transforming industries with its AI-powered blockchain architecture. It has diverse range of products for secure data management, asset tokenization, trusted social interactions….

The Fetch.ai platform uses a combination of blockchain, AI, and machine learning technologies to enable devices and services to communicate and collaborate autonomously. The goal is to create a more efficient and decentralized system for various applications, including smart cities, supply chain management, and more.

FET tokens can be staked, meaning they are temporarily locked up in the network. Staking is a way for token holders to help keep the network safe and earn FET tokens in return. Staking is an important part of many blockchain networks because it helps reach consensus and keep the network safe. In Fetch.ai, staking also grants access to additional features, such as participation in collective learning processes.

Products include;

AI Engine ecosystem –

Synergy of agent-based services and AI Engine ecosystem
The AI Engine allows users and developers to connect to a wide range of agent-based services. Once an agent is registered ↗️ the service provided is visible to the AI engine and it can start connecting users and services together.

This next-generation system boasts personalized capabilities thanks to the presence of an internal agent which harmonizes tasks efficiently. Indeed, the AI Engine internally spawns a personal agent for use and once you have given it your intent, it asynchronously starts working on your behalf.

At its core lies the immense power of LLMs (Large Language Models), driving the Engine’s understanding, coordination, and problem-solving proficiency.

Catalyzing connections
The AI Engine introduces users and developers into a unified ecosystem of agent-based services. Once registered within the system, the service becomes an integral part of the AI Engine’s landscape, orchestrating dynamic connections between users and services.

Unveiling the intent’s architecture
At the heart of the AI Engine’s operation lies a sophisticated architecture comprising two fundamental components: Objectives and Tasks.

Objectives: these are the foundation of the AI Engine’s efforts, encapsulating the general goals of users in natural language, feeding the purpose and direction of the Engine.

Tasks: a dynamic sequence of steps that fuels the achievement of the defined objectives. In their complexity, tasks involve resource allocation, temporal considerations, and interdependencies, efficiently executed by agent-based services.

Deconstructing tasks
The AI Engine’s essence is distilled into two profound functions:

Comprehension and planning: this core process takes the user’s objective and transforms it into a meticulously curated series of sub-tasks, each representing an integral step towards the desired final outcome. This orchestration can be unfolded autonomously or, in some cases, with the user’s input to validate tasks selection.

Context building: the AI Engine is a skillful collector and transformer of information, continuously enriching its understanding. Contextual building is a continuous effort, refining the knowledge landscape happening continuously throughout the session with the AI Engine. In other words, Context building is the continuous process in which additional information is collected and/or transformed in order to complete a task.

Agentverse

The Agentverse is a cloud-based IDE for developing and deploying AI agents. It is a powerful platform designed to help you engage with Fetch.ai’s AI Agents technology. It is an exciting platform showcasing the technology and tools serving as a portal to the broader uAgents Framework and its use cases.

The Agentverse provides a robust platform to create, test, and deploy agents adaptable to any of your needs. It provides a user-friendly interface and a set of tools and libraries that make it easy to build and train AI agents, as well as to integrate them with existing systems. It is particularly beneficial for Python-based developers who want to audit and modify an agent’s code and check its responses to real-time edits made onto it.

Users operating on the Agentverse can deploy their AI agents to the Fetch.ai network, where they can be discovered and be used to provide a wide variety of services and use cases.

Agentverse: Explorer
The Agentverse Explorer allows you to search and connect with other agents registered in the Almanac ↗️ contract. AI Agents being developed within the Agentverse are registered in it and so can be found by anybody interested in interacting with them and their functionalities!

Different types of agents
Every agent available and displayed on the Explorer can be a: Hosted, Local, or Mailbox agent.

Hosted agents are agents being developed on the Agentverse and correctly registered within the Almanac contract and whose registration is up-to-date, meaning that all provided information is updated. In this case the agent is denoted by a green Active tag. On the other hand, a Local agent is one pointing towards a local endpoint. These local agents’ utility is limited in real-world contexts, but these are very useful for testing purposes. Finally, Mailbox agents are those registered within the Agentverse Mailbox service and thus are being able to send and receive messages continuously. Agents which are not online are visible as Offline agents.

Agentverse: Mailroom / IoT Gateway

The Agentverse Mailroom service is a useful tool dedicated to set up mailboxes for your locally-run agents. This is with the aim of not having them online all the time to communicate with one another and run them independently of your constant presence to run the server.

Remote communication with the Mailroom
Through the Mailbox service, communication between agents registered in the Agentverse and local agents is made possible. In fact, your locally hosted agents can access the APIs to retrieve the information needed for communicating with the other agents registered within the Agentverse.

https://fetch.ai/