Agentfield

Agentfield is an open-source platform designed to be the infrastructure layer for AI agents. It's not a chatbot framework or a simple library; it's a backend service you deploy in your stack, similar to a database or message queue. Its core job is to let you build, orchestrate, and manage fleets of AI agents that can perform complex, multi-step tasks. You write agent logic in Python, Go, or TypeScript, and Agentfield handles turning those functions into callable, production-ready APIs. It manages the entire lifecycle: routing calls between services and agents, maintaining state for long-running processes, and scaling to handle thousands of concurrent agent interactions.

What sets Agentfield apart is its focus on the operational side of AI agents. It provides a unified control plane to govern everything. You get built-in tools for discovery, so services can find and call agents. It has a robust identity system using Decentralized Identifiers (DIDs) and Verifiable Credentials for security and audit trails. The platform also abstracts LLM complexity, giving you a single interface to call over 100 different models from providers like OpenAI, Anthropic, Google, and open-source options via Hugging Face. This means your agent logic stays the same even if you switch the underlying AI model.

This tool is built for developers and engineering teams who need to move beyond prototypes and deploy reliable, governed AI agent systems. It's particularly useful for scenarios requiring coordination between multiple specialized agents, such as real-time fraud detection that analyzes payment, identity, and behavior signals simultaneously. Other prime use cases include creating autonomous code review pipelines, building intelligent customer support triage systems, or orchestrating deep research agents that can process and synthesize information from vast numbers of documents. If you're building AI into the core workflows of your application, Agentfield provides the missing backend t