Planner
Spec
Reads the ticket, repository, docs, and prior PRs, then creates the implementation and testing plan the rest of the agent team ships against.
Your autonomous software team
Assign backlog tickets to SHIP's AI software factory. Your team of AI coding agents plans, builds, reviews and tests, then delivers a pull request with proof it works.
Sign up with GitHub or email. Your first missions are free, and no card is needed.
Works with the tools you use
GitHubLinearOpenAIClaude Code
Pi
PiThe problem
Agents already write a growing share of your production code. It lands faster than teams can verify its quality or account for its cost.
Teams pick their own agents, tools, and models, and nothing connects that choice to what ships or the uneven quality it ships at.
As agent adoption grows, that gap becomes unreviewed code, unpredictable spend, and outcomes no one can attribute. This is where teams lose control of quality and cost.
Quality control today
+91%
more review effort is spent checking AI-generated code, yet delivery outcomes improve only marginally.
Faros AI, 10,000+ developers across 1,255 teamsCost control today
148x
cost difference for the same task depending on the AI models and tools used.
Artificial Analysis Coding Agent Index, 2026: 23 harness x model stacks on 321 tasksThe solution
How SHIP restores control
SHIP is the only platform that runs coding agents like your team and proves what they ship and cost.
The agent team
Four specialists, on a mission
Your AI agent team collaborates on its shared mission. It navigates through the stages of your software development lifecycle.
Builder
Code
Writes the code in a sandbox. Runs your formatter, linter, typecheck, and tests, then pushes to the PR and watches CI, fixing failures before it passes.
Reviewer
Review
Reviews the diff against the plan and your project guidelines. Blocks critical issues, signs off on the rest.
Tester
QA
Runs your deployment pipeline out to an isolated preview, then walks the happy path and the unhappy ones. Validates acceptance criteria and shares proof of work.
Mission Control
See the return on AI investment
Monitor missions in real time and see the outcome of each agent and model. Compare how they perform, and route the work to the stack that delivers best.
Mission detail
Inspect the full timeline of a mission
Open a mission to follow its timeline end to end. Read what each agent did on its turn, its cost, and its result.
Verified PR
A gated, reviewed, and tested outcome
Every mission lands a pull request that already passed reviews and tests, with the agent identity on the record.
Proof of work
Review the outcome with visual proof
Screenshots, videos, and a test recording are the evidence attached to a completed mission. Accept or decline.
Cost optimization
Make every AI investment count
Measure your spend against the work delivered, and reduce cost systematically.
AI sovereignty
Own your stack, your keys, your rules
Run missions on the models, tools, and AI contracts your organization already uses.
Your contracts and keys
Bring your own AI contracts, keys, harness and models.
Connect your own provider accounts. Inference runs at your own contracted rates, directly on your account.
Zero-trust security model
Your secrets stay yours, encrypted at rest.
Agents run in an isolated sandbox and never receive your keys. An agent can access only what the task needs, and the platform attaches your credential at the network edge.
Data governance
Run inference in your own regions, on your own accounts.
Your provider accounts, contracts, and regions decide where inference runs. The session data that powers your logs, metrics, and audit trail is held under SHIP's own security controls.
Works with your stack
Keep the tools your team already runs
Start shipping faster and cheaper as soon as you onboard. SHIP lets your whole team deliver without learning anything new.
Launch your autonomous software team
Connect a repository and assign your first issue. Your first missions are free.
