An open-source control plane for building and scaling AI agents as production-ready backend services with identity, observability, and governance.
AgentField is an open-source control plane for building and scaling AI agents as production backend services. It transforms agent logic written in Python, Go, or TypeScript into infrastructure with automatic REST endpoints, cross-agent routing, async execution, and cryptographic audit trails. It solves the problem of managing non-deterministic AI workloads at scale with built-in observability and governance.
Developers and engineering teams building production-grade AI agent systems that need routing, coordination, tracing, and audit capabilities beyond simple chatbots or prompt orchestrators.
Developers choose AgentField for its production-ready infrastructure, built-in cryptographic identity and governance, and the ability to treat AI agents like scalable microservices. Its unique selling point is providing IAM for AI agents and verifiable audit trails, ensuring decisions are traceable and non-repudiable.
Build, run and scale AI agents like API and microservices - observable,auditable and identity-aware from day one.
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AgentField integrates Pydantic or Zod schemas with LLM calls to return typed, validated outputs, as shown in the code example where `app.ai(schema=Decision)` ensures structured decision-making.
It provides a control plane for routing calls between agents with full tracing and discovery, enabling complex multi-agent workflows like those in the autonomous engineering team example.
Every execution generates a tamper-proof, offline-verifiable credential using W3C DIDs, ensuring non-repudiation and governance, which is critical for production systems.
Supports fire-and-forget execution with webhooks and allows pausing for human approval via `app.pause()`, making it suitable for long-running, crash-safe tasks like claims processing.
Requires running a separate control plane service (e.g., via Docker or Kubernetes), adding operational complexity compared to lightweight, library-only frameworks.
As a newer project, it has fewer third-party integrations and community resources than established alternatives like LangChain, which might slow adoption for some teams.
The focus on cryptographic identity, governance, and production infrastructure concepts can be overwhelming for developers unfamiliar with decentralized identifiers or agent meshes.