SHIP

npx add-mcp 'https://mcp.letsship.ai/mcp'

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.

Start for free See how 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 CodePi

GitHubLinearOpenAIClaude CodePi

The 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%+91%+ 1 %

more review effort is spent checking AI-generated code, yet delivery outcomes improve only marginally.

Faros AI, 10,000+ developers across 1,255 teams

Cost control today

148x148x1 x

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 tasks

The solution

How SHIP restores control

Autonomous delivery

Operate AI agents that review and test as fast as they build, so work ships while your engineers stay in control.

Cost optimization

Monitor every step, compare performance, and optimize AI costs confidently.

AI sovereignty

Run missions on the models, tools, and AI contracts your organization already uses.

SHIP is the only platform that runs coding agents like your team and proves what they ship and cost.

Autonomous software delivery

Assign issues, get work done

Operate your AI agent team to bring software to production while your engineers stay in control.

Assign

Assign work to the SHIP agent on an issue

Work starts the moment you assign the issue. Delegate work to your AI agent team and walk away.

Collaborate

Chat with the agent team, right on the issue

Steer the work in the thread you are already in. Ask for a follow-up, or get a mission report.

Stay in the loop

Notifications as the work advances

Each stage reports back as it completes, so you read progress where you already track it.

SHIPnow

STB-526 Improve the lighthouse SEO score of the home page

On it: planning the work, implementing it, and opening a PR.

SHIP7m ago

letsship/ship-bench-app #373

SHIP opened a pull request.

SHIP7m ago

letsship/ship-bench-app #373

All CI checks have passed.

SHIP7m ago

letsship/ship-bench-app #373

Reviewer rejected with 2 critical issues.

SHIP7m ago

STB-526 Improve the lighthouse SEO score of the home page

Deployment succeeded. Preview environment is ready for testing.

SHIP3m ago

STB-526 Improve the lighthouse SEO score of the home page

Code review and QA passed. Mission is ready for acceptance.

The agent team

Six specialists, on a mission

Your AI agent team collaborates on its shared mission. It navigates through the stages of your software development lifecycle.

Researcher

Context

Reads the ticket, repository, docs, and prior PRs. Surfaces ambiguity before anyone writes code.

Planner

Spec

Creates the implementation and testing plan the rest of the agent team ships against.

Builder

Code

Writes the code in a sandbox. Runs your formatter, linter, typecheck, and tests, fixing failures before submission.

Reviewer

Review

Reviews the diff against the plan and your project guidelines. Blocks critical issues, signs off on the rest.

Operator

DevOps

Pushes to the PR, monitors CI, and runs your deployment pipeline out to an isolated preview.

Tester

QA

Walks the happy path, then the unhappy ones. Validates acceptance criteria and shares proof of work.

01PlanResearcher, Planner02BuildBuilder, Operator03ReviewReviewer04DeployOperator05TestTester

1. 01 Plan Researcher, Planner
2. 02 Build Builder, Operator
3. 03 Review Reviewer
4. 04 Deploy Operator
5. 05 Test Tester

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.

Planning

Improve the lighthouse SEO score of the home pageSTB-526

letsship/ship-bench-app

15s $0.05

Building

Migrate the settings page to server componentsSTB-517

letsship/ship-bench-app

48s $0.37

Building

Add rate limiting to the public APISTB-541

letsship/ship-bench-app

1m 20s $0.32

Reviewing

Add idempotency keys to the checkout endpointSTB-560

letsship/ship-bench-app # 401

2m 10s $0.62

Testing

Fix the N+1 query on the orders dashboardSTB-498

letsship/ship-bench-app # 352

5m 05s $0.97

Ready to merge

Add optimistic UI to the comment formSTB-534

letsship/ship-bench-app # 379

13m 20s $1.28

Ready to merge

Fix the memory leak in the WebSocket clientSTB-489

letsship/ship-bench-app # 344

16m 40s $1.35

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.

Mission logSTB-526 - PR # 373

merged

16m 48s

Cycle time

pickup to mission complete

19m 52s

Lead time

issue created to merged

$1.76

Total inference cost

attributed by stage

184.5k / 28.0k

Tokens (in / out)

across all stages

4

Agent turns

across the mission

Stage	# of turns	Duration	Share	Cost
Plannerclaude-code/opus - 15.6k in - 7.8k out	1	1m 47s	13.8 %	$0.351
Builderclaude-code/haiku - 29.3k in - 9.1k out	1	5m 17s	41.1 %	$0.189
Reviewerclaude-code/opus - 96.5k in - 3.0k out	1	49s	6.3 %	$0.687
QAclaude-code/sonnet - 43.1k in - 8.1k out	1	3m 49s	29.7 %	$0.530
CI	1	1m 10s	9.1 %	-

*From a real mission operated on SHIP. Actual duration and cost vary by project complexity, harness, model, and per-role agent configuration, and lead time depends on acceptance speed.

Compare and choose

The same issue, priced across your choice of agents and models.

Read our SWE-in-a-team benchmark research.

Total cost per mission ($)*One real issue from SHIP's own SWE-in-a-team benchmark, resolved by every configuration shown to a done state. Planner, reviewer and QA are pinned to the same model, only the builder changes. Cost is measured per token at published list prices.

86420

pi glm-5.2pi deepseek-v4-flashclaude-code haikuopen-code glm-5.2codex gpt-5.6-solclaude-code fablepi - glm-5.2Cost : $1.37

Cycle time (min)*Wall-clock for that same ticket, from first dispatch to a done issue, and a ready-for-acceptance PR.

403020100

pi glm-5.2pi deepseek-v4-flashclaude-code haikuopen-code glm-5.2codex gpt-5.6-solclaude-code fablepi - glm-5.2Cycle time : 31 min

Budget

piglm-5.2pideepseek-v4-flashclaude-codehaikuopen-codeglm-5.2

Frontier

codexgpt-5.6-solclaude-codefable

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.

Configure agents and models per role

Planner

Claude Codeopus

Builder

glm

Reviewer

Codexgpt

QA

Pikimi

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.

Agentisolated sandbox placeholder

Your keyson the platform anthropic github

your key
attached at the edge

provider

Your keys never enter the sandbox: the request carries a placeholder, and the platform swaps in your real key at the network edge. Capability-based access is granted when necessary over a short-lived, scoped token.

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.

• SOC 2 Type II*
• GDPR*
• HIPAA*

* Compliance in progress.

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.

Your agentic engineering system

Use the agents, skills, MCP servers, project memory and tools your team already built.

Your issue tracking system

File the issues in your existing projects as you're assigning them to a new team member.

Your repositories and pipelines

Completed work ships to your existing repositories using your CI/CD, following your own SDLC model.

What SHIP adds

Your autonomous software team, which works in the systems you already use.

Launch your autonomous software team

Connect a repository and assign your first issue. Your first missions are free.

Start for free

The SHIP agent team at sea

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