Deploy AI agents that code in parallel
Dispatch agents to isolated cloud VMs. They plan, code, and test — you verify and ship.
Fleet Overview
Plan
Build
Test
Review
Plan
Build
Test
Review
Plan
Build
Test
Review
Session View
Pipeline
Agent asks
"I found 2 existing OAuth implementations. Should I extend the existing GitHub OAuth flow or create a new provider-agnostic handler?"
Live Output
$ fleet deploy --repo webapp --task "Add OAuth login"
Provisioning isolated VM... done
Cloning repository...
Agent analyzing codebase (1,247 files)...
Planning phase complete. 6 steps identified.
Writing src/lib/server/auth/oauth.ts
Writing apps/web/src/routes/auth/callback/+server.ts
Running test suite... 18/18 passing
⏸ Awaiting human verification before PR creation
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You're coordinating agents by hand
Running AI agents across multiple tasks means juggling terminals, credentials, and blind spots.
Switching between terminals to check agent status
Copy-pasting API keys into every new session
No visibility into what your agents are actually doing
How it works
Five steps from idea to merged PR.
Deploy
Select a repo and task, click Deploy
AutomatedPlanning
Agent analyzes your codebase and creates a plan
AutomatedWorking
Agent writes code in an isolated cloud VM
AutomatedYou Verify
Review changes, answer questions, approve or redirect
YouShip
Agent creates a PR, you merge
ResultBuilt for parallel AI development
Parallel Agents
Run multiple agents simultaneously. Each gets its own isolated VM.
Structured Pipeline
Every agent follows Planning, Working, Testing, Review. No black boxes.
Human-in-the-Loop
Agents pause for verification. You are always the final QA.
Simple pricing
Start for free. Scale as you grow.
Pro
- 5 parallel engineers
- Priority support
- Unlimited sessions
- Private repos
Scale
- Unlimited parallel engineers
- Dedicated support
- Custom VM specs
- SSO & audit logs
Ready to deploy your first agent?
Join the waitlist. We'll let you know when Fleet is ready.