Anter: Build AI agents. Ship them as APIs.
Anter is the AI agent builder for engineering teams. It's a managed multi-agent orchestration engine, visual builder, and streaming API — ship AI-powered features without months of custom infrastructure work.
Your prototype works. Now make it production-ready.
Free to start · No credit card · First agent running in minutes · 1M free tokens, then bring your own model key
Connect your preferred LLM provider — or route across multiple
What is Anter?
Anter is an enterprise-grade managed AI agents platform and runtime system for building, orchestrating, and shipping autonomous multi-agent systems as production streaming APIs. It combines visual agent building with deterministic routing, multi-LLM support, and end-to-end execution tracing without requiring teams to build custom hosting infrastructure.
Route complex workflows across specialized sub-agents using validated transfer and delegation protocols with auditability.
Integrate Model Context Protocol (MCP servers) and REST APIs with zero-trust permission modes and execution step budgets.
Native SSE streaming, state replay from any checkpoint, and OpenTelemetry tracing across OpenAI, Anthropic, Azure, and Google models.
Why Anter
Most teams start with a prototype.
Then production happens.
Building an AI agent takes a weekend. Shipping one that works reliably, scales with your users, and doesn't page you at 3am — that's the hard part.
It breaks and you can't see why.
No observability. Routing failures are invisible. You can't replay what the agent did or why it took a wrong turn. Every production incident is a black box.
Anter gives every run a durable audit trail, streaming replay from any checkpoint, and OpenTelemetry tracing across every tool call and handoff.
Your routing logic doesn't scale.
Single-agent systems hit a ceiling fast. Multi-step workflows need real transfer and delegation semantics — not chained prompts you hope hold together.
Anter's orchestration engine handles transfer, delegation, and fallback with routing graphs validated at both write-time and runtime. Every decision is audited.
You're building infra instead of product.
Redis session management, SSE streaming, multi-LLM routing, approval gates, tenant isolation — these aren't differentiated features. They're table stakes that eat your roadmap.
Anter ships all of it pre-built and production-tested, so your team stays focused on the AI behavior that actually matters to your users.
Why not the alternative
Anthropic and OpenAI will sell you a model with an agent bolted on.
We built the agent.
The model providers ship multi-agent primitives — coordinators, handoffs, approval hooks. Whether they're validated, audited, and safe to leave unattended is left for you to build. The agent frameworks hand routing decisions to the LLM and hope it holds. Anter's orchestrator validates every handoff twice, persists it atomically, and bounds runaway agent-to-agent chains by design.
Fail-closed by default, not bolted on.
A pending tool approval in most agent SDKs just waits for a human to show up — no built-in timeout, escalation, or auto-deny if nobody does. Anter fails closed automatically: an unattended or scheduled run auto-denies anything that needs a human's OK.
Routing you can prove, not routing you hope for.
A 'manager agent' deciding who goes next is still just an LLM guessing. Anter validates every transfer and delegation against a write-time allowlist and a runtime existence check — and won't let your front-door agent fabricate an answer instead of routing.
Bounded, not just built.
Agent-calls-agent chains are a real cost and latency risk — deep chains, accidental cycles, unbounded recursion. Anter enforces an exact cycle guard, a hop-depth ceiling, and step-budget decay on every cross-agent dispatch.
Platform capabilities
Everything you'd build anyway.
Already built.
Production-grade AI agent infrastructure — from the execution engine to the UI library to the streaming API — without the months of plumbing.
Multi-Agent Orchestration
Transfer and delegate across named sub-agents with validated routing graphs and a per-hop audit trail. Every handoff is persisted atomically — no orphaned runs.
How transfer and delegate routing worksWhite-Label React UI
Embed the full agent-management console inside your own product — themed to your brand, behind your auth and router, no iframe. A typed adapter wires it to your host app (routing, auth, transport). The companion chat SDK drops the end-user chat into any site.
Embeddable React AI chat widgetMCP + Tool Integration
Connect any MCP server (SSE or Streamable HTTP) or define HTTP tools with per-property session injection. The LLM never sees tenant IDs — they're injected silently at call time.
Run MCP agents on a managed platformTriage-First Skill Routing
The ReAct engine loads specialist skills on-demand via a virtual load_skill tool. No pre-flight LLM call — triage runs inside the loop with full context and zero extra cost.
Skill loading and triage docsStreaming + Replay
SSE streaming with monotonic chunk writes and a deduplicated replay endpoint. Reconnect mid-run from any index without triggering a duplicate execution.
Resume and replay a streaming runFull Observability
Per-run OpenTelemetry spans, Prometheus-style metrics, and a step-by-step execution trace. Every tool call, every routing decision, every token — inspectable.
Inspect the routing timelineMulti-agent routing
Orchestration you can
reason about.
Transfer hands off full ownership. Delegation sends a subtask and returns. Both are validated at write-time, enforced at runtime, and recorded as durable routing events — so you always know exactly what happened and why.
Every routing decision is recorded. Every handoff is validated. Every run is replayable.
How it works
From idea to production
in three steps.
Build
Design your agent graph in the visual builder. Configure skills, tools, and sub-agent routing topology. Define which LLM provider each agent uses.
- Visual agent graph editor
- Skill and tool assignment
- Multi-LLM provider routing
Connect
Wire up MCP servers, HTTP tools, or your own APIs. Set context requirements and approval gates. Encrypted credential storage for every provider.
- MCP server integration
- HTTP tool definitions
- Approval gates per tool
Deploy
Generate a project API key and stream agent responses from a single endpoint. Replay any execution. Observe every run in the timeline.
- Project-scoped API keys
- SSE streaming endpoint
- Execution replay & tracing
Live walkthrough
See Anter running
real workflows.
A real recording of the product — no mock screenshots. Watch a managed agent handle orchestration, routing, tool calls, and observability, live.
Open the full demo with chaptersWhat's happening now
The key signal is traceability, not a single latency number. You can inspect timing and routing at each step.
Ship fast
One endpoint.
Your agent, streaming anywhere.
A project API key and a single POST /run-stream call. SSE chunks arrive in real time. Reconnect from any index with the replay endpoint.
curl -N -X POST \
"https://api.anter.ai/v1/external/agent-runner/agents/:id/run-stream" \
-H "x-project-id: proj_..." \
-H "x-api-key: proj_api-key_..." \
-H "Content-Type: application/json" \
-d '{"message": "Summarize the key risks for this quarter.", "userId": "user_123"}'The stream supports both the Vercel AI SDK format (Accept: ai-sdk=v1) and a plain SSE format — pick what fits your client stack.
Add "Built on Anter" to Your Repo
Running your AI agents on Anter? Showcase your integration on GitHub, documentation sites, or blog posts with our official badge.
Stop building infrastructure.
Start shipping agents.
Free to start. No credit card required. Your first agent is running in minutes — not months. 1M free tokens included; bring your own model key after that.
Free tier · No credit card · 1M free tokens, then bring your own key · Production-ready from day one