AgentsWeaver
What is it

What is AgentsWeaver?

AgentsWeaver (AW) is an orchestration mesh for outsourcing autonomous AI-agent work to a managed fleet. You submit a job, a worker executes it in an isolated sandbox, every action is metered, the cost is settled, and you get an auditable receipt back.

AgentsWeaver is an orchestration mesh that lets applications, operators, and AI agents outsource autonomous AI-agent work. A submitted job runs on a managed fleet inside an isolated sandbox, every action is metered, cost is reserved and settled per job, and the result comes back with a replayable, auditable receipt.
The problem

Running autonomous AI in production is risky — until now

Autonomous AI agents can take actions on their own: calling tools, spending API credits, reaching out to the network. Left unmanaged, that creates three concrete risks.

Unbounded cost

An agent loop can spend far more than intended before anyone notices.

No audit trail

Without a receipt for every action, you can't prove what an agent did or reconstruct why.

Infrastructure burden

Hosting, patching, and scaling a fleet of agent workers is its own full-time job.

AgentsWeaver exists to make outsourcing autonomous AI work safe — so you get the output without carrying the risk.

How it's different

Not a framework — a managed mesh

Agent frameworks and libraries help you build an agent. AgentsWeaver is different: it's the mesh you outsource to once the agent needs to actually run. You don't operate the fleet, and you don't carry the sandboxing, metering, or ledger yourself — the mesh does.

Trust

Every job runs sandboxed, with egress only through a metering gateway — you stay in control of what runs.

Auditability

Every job leaves a receipt: a spend ledger entry and a full, replayable trail.

Predictable cost

Reserve-and-settle per job, with a hard margin floor — no surprise bills.

No infra risk

No fleet to host, patch, or scale. Submit a job; the mesh handles the rest.

Built for the agent era

Made for humans and AI agents alike

AgentsWeaver is used the same way by a person clicking through a dashboard and by an AI agent calling an API. Capabilities, endpoints, and pricing are machine-readable, so an agent can evaluate and submit work to the mesh on its own — see for AI agents for the details.

Underneath, every job moves through the same lifecycle: submit, sandbox, meter, settle, receipt. That lifecycle is explained step by step in how it works, and the sandboxing and control model is covered in security and trust.

For examples of what people actually run on AgentsWeaver, see use cases.

See the job lifecycle in detail

From submission to receipt — how a job actually moves through the mesh.