Platform Overview

How Agentfield's control plane shapes autonomous software.

Platform Overview

How Agentfield's control plane shapes autonomous software for production systems

When AI becomes part of your software stack, you need a control plane that treats intelligent agents like microservices-distributed, observable, and governable. Traditional frameworks work for prototypes. They break in production.

Traditional Agent Frameworks

Monolithic Agent App

  • •Durable Queues (DIY)
  • •Async Execution (DIY)
  • •API Gateway Wrapper (DIY)
  • •State Management (DIY)
  • •Observability (DIY)
  • •Auth & Identity (DIY)

You have to build and maintain the entire infrastructure stack

Evolution

Agentfield

Control Plane

•Orchestration
•Workflows
•Memory
•Observability
•Identity
•API Gateway

Agent Nodes

Marketing Agent
Marketing Team
Running
Support Agent
Support Team
Running
Analytics Agent
Analytics Team
Running

Deploy independently

Share memory automatically

Kubernetes-like orchestration

The Challenge

Existing agent frameworks build AI as isolated applications. But autonomous software needs the same infrastructure patterns that made microservices successful: service discovery, distributed state, identity, and observability.

What Agentfield Provides

Distributed Architecture

Control plane + independent agent nodes. Teams deploy agents independently without coordination bottlenecks.

API-First Design

Every agent function automatically becomes a REST endpoint. Works with React, Python, .NET, mobile apps—any stack.

Zero-Config Memory

Shared state across distributed agents. Automatic scoping and synchronization. No vector stores to configure.

Cryptographic Identity

DIDs + Verifiable Credentials issued automatically. Prove what every agent decided with tamper-proof records.

Observable by Default

Workflow DAGs, execution traces, and agent notes. Understand why intelligent systems made decisions.

Production Ready

Docker/Kubernetes ready. Durable queues, async execution with no timeout limits (hours/days for nested workflows), webhooks, metrics, and health checks built in from day one.

Ready to Deploy?

From laptop to production in minutes. Agentfield's stateless control plane and independent agent nodes scale from af server on localhost to Kubernetes clusters handling billions of requests—same code, zero rewrites.

Deployment Overview

Understand the architecture: stateless control plane, independent agent scaling, and zero infrastructure dependencies

Start Local

Zero-config development with embedded BoltDB. Just af server.

Think of It This Way

Traditional agent frameworks are like Flask—great for building a single application.

Agentfield is like Kubernetes + FastAPI—infrastructure for building distributed autonomous software.

You write agents as typed Python functions. Agentfield handles orchestration, memory, identity, and observability.

Built For Teams That Need Scale

Agentfield is designed for production multi-agent systems where:

  • Multiple teams build and deploy agents independently
  • Different agents need to coordinate and share state
  • Compliance teams require cryptographic proof of decisions
  • Frontend/mobile apps need to integrate via standard APIs
  • Operations teams need observability and production guarantees

If you're building a chatbot prototype, traditional frameworks work fine.

If you're building production autonomous software, you need infrastructure.

Get Started in 5 Minutes

Build Your First Agent

Follow our quick start guide to create and deploy your first Agentfield agent in minutes.

Why Agentfield vs Frameworks

Understand how Agentfield differs from traditional agent frameworks and when to use each.

Works on macOS, Linux • Docker/Kubernetes ready • Open source, Apache 2.0