Agentfield

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agentfield is an open-source AI Agents & Automation tool that helps build, run, and scale AI agents like APIs and microservices. It provides observable, auditable, and identity-aware infrastructure for backend AI agents.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is agentfield?

AgentField is an open-source control plane designed to build, run, and scale AI agents as production-ready APIs and microservices. It allows developers to write agent logic in Python, Go, or TypeScript, transforming it into robust infrastructure with features like routing, coordination, memory, async execution, and cryptographic audit trails. Every function becomes a REST endpoint, and each agent receives a cryptographic identity, ensuring every decision is traceable. AgentField supports structured AI output, human-in-the-loop approvals, cross-agent calls, and canary deployments. It also offers comprehensive observability, identity and access management, and verifiable credentials for tamper-proof execution receipts.

Best used for

Ideal for developers and product managers who need to build and deploy AI agents as reliable backend services, manage their lifecycle, and ensure auditability. Especially valuable for creating complex, multi-agent systems requiring human approval, version control, and secure, traceable execution.

Common actions

build AI agents

deploy AI agents

manage AI agents

automate workflows

integrate AI services

collaborationlow-code/no-codedeepfakeopen-sourceworkflowsautomated workflowface swappinggithub copilot"AI Agents"

Capabilities

Key features

Build AI agents
Run AI agents
Scale AI agents
Cryptographic audit trails
Human-in-the-loop
Canary deployments

Target Audience

developerproduct managerstartup founder

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What programming languages does AgentField support for building agents?

AgentField supports building agent logic in Python, Go, and TypeScript. This allows developers to use their preferred language to create and integrate AI agents into their existing systems and workflows.

How does AgentField ensure the auditability and traceability of AI agent decisions?

AgentField provides cryptographic identities for every agent and generates verifiable credentials for each execution. This creates a tamper-proof audit trail, ensuring every decision and action taken by an agent is traceable and verifiable.

Can AgentField integrate human approval into AI agent workflows?

Yes, AgentField includes a human-in-the-loop feature with `app.pause()`. This allows agents to suspend execution, notify human reviewers via webhooks, and resume once approval is granted, ensuring critical decisions are reviewed.

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