AI Orchestration Platform

Orchestrate AI agents you can actually debug.

Durable multi-agent workflows with full-trace observability. Run fleets of agents as trees and DAGs — and replay every node, every loop, every token.

Start buildingRead the docs
SOC 2 Type II·Self-host or cloud·OpenTelemetry-native
run_8f31a2 · livecheckout-flow · v2.4
Planner
Agent
0.8s3.1K
Coder
Agent
1.2s$0.004
Reviewer
Agent
×3
The control plane

One platform from prompt to production.

Durable orchestration

Trees, DAGs, branching, loops and shared state — written as plain code, executed durably. Crash mid-run and resume exactly where you left off.

Full-trace observability

Every agent step is an activity, tagged and traced. Join OTel spans to runs and watch latency, cost and tokens per node.

Pluggable model routing

Alias-based, layered config from platform to tenant to experiment. Flip models with a data change — never a deploy.

Governed & secure

Agent- and workflow-level permissions, a built-in secret vault, and encrypted worker I/O. Multi-tenant by design.

Built for engineers

Define agents in code. Run them durably.

A run-centric SDK and REST API: start, stream, signal, cancel. The console gives you the live trace for free.

Explore the SDK
quickstart.pypython
from infraweave import Workflow, agent

@agent("coder", model="tier-1-reasoning")
async def coder(ctx, task):
    return await ctx.llm.complete(task.prompt)

wf = Workflow("checkout-flow")
run = await wf.start(input={"task": "ship it"})
print(run.url)  # live trace in the console
Workflow runs / day
48M
Median overhead
6ms
Uptime SLA
99.99%
Model providers
40+

Weave your agents together.

Start free. Self-host or run on InfraWeave Cloud.

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