AgentField is an open-source AI backend designed to transform autonomous software agents into scalable, observable, and governable microservices. By providing a robust control plane, AgentField enables developers to deploy AI agents as production-grade services, ensuring seamless integration with existing infrastructures and facilitating efficient orchestration, identity management, and observability. Key Features and Functionality: - Agent-as-a-Microservice Architecture: AgentField allows developers to encapsulate AI agents as microservices, offering auto-generated OpenAPI specifications, a unified API gateway, and language-agnostic connectivity. This approach ensures that agents can be deployed independently while sharing memory automatically, akin to Kubernetes-style orchestration. - Built-in Identity, Trust, and Audit: Each agent is assigned a cryptographic identity (Decentralized Identifier or DID), and every action is signed, creating a tamper-proof audit trail (Verifiable Credential or VC). This mechanism provides verifiable proof of agent activities, enhancing trust and compliance. - Independent Deployment with Central Coordination: Teams can deploy agents on their own timelines, while the control plane manages discovery, routing, and a zero-configuration shared memory fabric. This setup allows agents to coordinate automatically without monolithic coupling. - Comprehensive Production Infrastructure: AgentField offers a complete production infrastructure, including durable queues, asynchronous execution with no timeout limits, webhooks, built-in load balancing, and health checks. It is Docker and Kubernetes ready, facilitating seamless integration into existing systems. Primary Value and Problem Solved: AgentField addresses the challenges of scaling and governing autonomous software agents in production environments. Traditional agent frameworks often fall short when transitioning from prototypes to production due to issues like lack of scalability, observability, and secure identity management. AgentField bridges this gap by providing a control plane that treats intelligent agents like microservices, ensuring they are distributed, observable, and governable. This infrastructure empowers developers to build, scale, and manage AI agents effectively, enabling the creation of robust, production-ready autonomous systems.