Governed autonomy for agent fleets

Govern the outcome. Leave the path to the agents.

Midfleet is the coordination, orchestration, and governance runtime for autonomous AI work. Set outcomes and boundaries once. Agents move work forward within visible constraints - with ownership, exceptions, approvals, and evidence on the path to completion.

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Autonomous work stays owned, scoped, reviewed, and visible.

Why Midfleet

Different layer than traces or builders.

Alternatives help you inspect agents or create them. Midfleet governs the work itself - so completion is controlled even when agents stay autonomous.

Trace & eval tools

Know what an agent did after it ran.

  • Step traces, latency, cost, quality scores
  • Debug failures and regressions in runs
  • Framework-agnostic observability

Still missing

  • No shared outcome ownership across agents
  • No completion gate tied to evidence
  • Does not stop unfinished work from shipping

Agent builders

Create and launch agents into tools you already use.

  • Agent setup, tools, and channel deploy
  • Per-action approvals on sensitive tools
  • Faster path from idea to a running agent

Still missing

  • Weak multi-agent run state on one outcome
  • Limited durable boundary around repos/systems
  • Hard to inspect blocked -> waiting -> done paths

Midfleet

Control how autonomous work completes.

  • Outcome + boundary defined once by the team
  • Agents execute freely inside that boundary
  • Ownership, exceptions, approvals, evidence on the path
  • Completion stays gated until configured proof clears
outcome boundary owner blocker evidence gate

How it works

Your team sets the outcome. Agents choose how to deliver it.

Not a forced workflow script. A control loop: humans define done and constraints; agents execute; Midfleet keeps durable state until completion is allowed.

You set intent and constraints
Agents choose path and tools
Midfleet holds state and gates
  1. 01

    Define the outcome

    You

    State what done means - deliverable, scope, and success criteria the team will accept.

    writes outcome.defined sets success criteria
  2. 02

    Set boundaries and protections

    You

    Declare what agents may change, what must be preserved, and which systems stay off-limits.

    writes boundary.held protects systems / paths
  3. 03

    Let agents reason and execute

    Agents

    Keep your runtimes, models, and tools. Agents stay free in how they work inside the boundary - no predetermined route.

    tracks owner + step attaches evidence surfaces blockers
  4. 04

    Require reviews and evidence

    Midfleet

    Configured approval gates and attached proof become part of completion. Work stays blocked until the gate clears.

    holds gate.blocked requires evidence + approval allows complete

In practice

A governed engineering outcome in the hub.

Live hub state shows who owns each step, what is done, what needs attention, and what is waiting - before work can complete.

midfleet GitHub epic #1486 governed run

Ship the accepted repository change inside the approved scope.

Epic refinement and implementation · evidence required before completion

Blocked Needs Attention 43h 15m

Run progress

Step 3 of 4 · Verify evidence

Refine Epic Analysis agent Done
Implement approved scope Implementation agent Done
Verify evidence Verification agent Needs attention
Independent review Independent reviewer Waiting
Live Hub state

Operator surfaces

Control active work. Resolve exceptions. Verify outcomes.

Not a feed of agent chatter. Each surface answers an operator question with durable state: who owns it, what is blocked, and what proof is attached.

01 · control

Control active work

Scope, ownership, active agents, and progress on the outcomes that matter.

02 · exceptions

Resolve exceptions

Blockers, ownership conflicts, and configured approvals surface with context for human decision.

03 · verify

Verify outcomes

Reviews, tests, evidence, and runtime history stay attached before completion.

Compatibility

Keep your agents. Add the control layer.

Midfleet works around existing agent runtimes, models, and tools. Agents keep their own reasoning and execution while Midfleet adds shared identity, operating state, boundaries, exceptions, and proof.

Your stack

Runtimes, models, and tools you already operate.

Midfleet adds

Identity, boundaries, exceptions, approvals, and evidence on the path to done.

Result

Autonomous execution with operator-grade completion control.

Deploy

Bring us the workflow. We shape the control path.

Deploy controlled agentic workflows into your engineering team - through forward-deployed engineering or self-serve. Talk to us when you need a governed path designed with your stack.

Forward-deployed engineering

We provision infrastructure and agents, integrate your environment, configure controls, and operate governed work end to end.

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Self-serve

Create a workspace, connect a repository, define the boundary, connect an agent, and run the first governed outcome.

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