Kubernetes for AI Agents
Build and run AI like microservices - scalable, observable, and identity-aware from day one.
A New Backend for a New Kind of Software
Not a toolkit. A complete backend for autonomous agents. No glue code needed.
Agents as Microservices
Every agent runs as an API with its own endpoints, schemas, and versioning — no glue code or routing setup required.
Built-in IAM and Audit
Cryptographic identity for every agent. Every action is cryptographically signed and permanently auditable.
Teams Deploy Independently
Each agent deploys independently with its own version and scaling. Automatic service discovery—no manual routing.
Deploy Like Real Software
Production operations baked in. Health probes, webhooks, auto-retry, and monitoring—ready from day one.
Write Code, Get Infrastructure
Functions become APIs. Calls create audit trails. Notes stream live to users.
Agent Cryptographic Identity & Audit Trails
Every execution generates a tamper-proof Verifiable Credential. Regulatory-compliant, offline-verifiable proof—not just logs that can be edited.
Learn more →Live Progress Tracking (SSE)
Real-time updates stream to your frontend via Server-Sent Events. Track multi-hour workflows with ctx.workflow.progress()—no polling, no WebSockets config.
Learn more →Secure Inter-Agent Communication
A simple ctx.call triggers a secure, server-side workflow. The controlplane automatically verifies the caller's identity (DID) and records the interaction as a tamper-proof Verifiable Credential.
Learn more →Multi-Hour Autonomous Workflows
Runs for hours or days with no timeout limits—unlike Lambda or traditional frameworks. Perfect for document processing, batch analysis, or complex orchestrations.
Learn more →Parallel Multi-Agent Coordination
Three specialized agents analyze simultaneously across distributed services. Automatic discovery, routing, and load balancing—no manual orchestration required.
Learn more →Guided AI Autonomy
AI makes autonomous decisions within structured guardrails using schema validation. Not just prompts—intelligent reasoning with predictable outputs.
Learn more →Identity and Infrastructure, Solved
Cryptographic DIDs for trust. Zero-config deployment for scale. The foundation autonomous software needs.
Identity for Autonomous Actors
Traditional IAM identifies humans. AI agents need cryptographic identity—DIDs for authentication, VCs for authorization, verifiable credentials for every action.
Agentfield makes identity infrastructure. Every agent gets a DID at registration. Every decision generates a signed VC. Control access. Prove actions. Verify offline.
Cryptographic IAM
DIDs for identity, VCs for authorization, policy enforcement
Verifiable Provenance
Export credential chains, verify independently

Beyond Frameworks, Beyond Auth
What frameworks can't deliver and identity providers weren't built for. See how coordination, identity, deployment, infrastructure, and observability stack up.
Agent Field Advantage
Automatic coordination
Integration Tax
To match Agent Field's built-in capabilities, you would need to integrate and maintain:
| Capability | Traditional Stack | Agent Field |
|---|---|---|
Service Discovery & Load Balancing # No hardcoded URLs, no manual registry
result = await app.call("other-agent.function")
# Control plane discovers agent location
# Load balances across instances | Agent Frameworks Consul/etcd + config Identity Frameworks Not applicable | Automatic discovery |
Cross-Agent Communication # Agent A calls Agent B (different team, different deploy)
sentiment = await app.call("sentiment-agent.analyze")
# Context propagates automatically
# Full DAG visibility | Agent Frameworks REST + service mesh Identity Frameworks Not applicable | Zero-config calls |
Automatic Workflow DAGs # Every app.call() creates DAG edge
# Parent-child relationships tracked
# Visualize: which agent called which
curl .../workflows/{id}/dag | Agent Frameworks Custom tracking Identity Frameworks Not applicable | Auto-generated |
Shared Memory Fabric # Agent A sets state
await app.memory.set("customer_risk", 8.5)
# Agent B reads it (same workflow)
risk = await app.memory.get("customer_risk") | Agent Frameworks Redis + sync logic Identity Frameworks Not applicable | Zero-config state |
Event-Driven Coordination @app.memory.on_change("customer_*_status")
async def react(event):
if event.value == "escalated":
await app.call("alert-agent.notify") | Agent Frameworks Kafka/RabbitMQ Identity Frameworks Not applicable | Memory change events |
Context Propagation # Session/workflow IDs flow automatically
# No manual header passing
# Complete distributed tracing | Agent Frameworks Pass correlation IDs Identity Frameworks Not applicable | Automatic flow |
Integration Tax
To match Agent Field's built-in capabilities, you would need to integrate and maintain:
Agent Field Advantage
Automatic coordination
Every Agent Has Cryptographic Identity
Decentralized Identity (DID)
Every agent gets a cryptographic passport
Verifiable Credentials (VC)
Every action is cryptographically signed
Tamper-Proof Audit
Export tamper-proof audit trails for compliance
Zero-Trust Architecture
Identity-based policies, not hope
Complete Feature Set
The world's best developer experience for building autonomous agents. Zero configuration, infinite scale.
Functions → REST APIs
Instant microservices from Python functions.
Auto-Routing & Discovery
Service mesh scaling without config.
Runtime Capability Discovery
Build AI orchestrators with dynamic tool selection.
Zero-Config Memory
Shared state without Redis setup.
Built-in Vector Search
Semantic search without vector DBs.
Agent Identity
Cryptographic decentralized identity for agents.
Verifiable Credentials
Tamper-proof execution proofs.
Async + Webhooks
Serverless-style async tasks via HTTP.
The Future of Software Is Autonomous - and Open
The next generation of systems won't just execute, they'll reason, coordinate, and prove. Let's build the open foundation together.
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