Assign
Assign work to the SHIP agent on an issue
Work starts the moment you assign the issue. Delegate work to your agent fleet and walk away.
TurnissuesintoreviewedandtestedPRsTurnissuesintoreviewedandtestedPRs
Assign an issue to SHIP. Agent team of specialists autonomously covers your SDLC, following your engineering practices, verifying, proving, and reporting every change.
For teams shipping software with coding agents.
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
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 fleet of AI agents for bringing software to production while your engineers stay in control.
Collaborate
Chat with the fleet, 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.
The fleet
Six specialists, on a mission
Your agent fleet collaborates on their shared mission. They navigate 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 fleet 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.
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.
Mission logSTB-526 · PR #373
merged16m 48s
Cycle time
19m 52s
Lead time
$1.76
Total inference cost
184.5k / 28.0k
Tokens (in / out)
4
Agent turns
| Stage | # of turns | Duration | Share | Cost |
|---|---|---|---|---|
| Plannerclaude-code/opus · 15.6k in · 7.8k out | 1 | 1m 47s | $0.351 | |
| Builderclaude-code/haiku · 29.3k in · 9.1k out | 1 | 5m 17s | $0.189 | |
| Reviewerclaude-code/opus · 96.5k in · 3.0k out | 1 | 49s | $0.687 | |
| QAclaude-code/sonnet · 43.1k in · 8.1k out | 1 | 3m 49s | $0.530 | |
| CI | 1 | 1m 10s | - |
From a real mission operated on SHIP. Actual duration and cost vary by project complexity, harness, model, and per-role agent configuration, and lead time depends on acceptance speed.
Compare and choose
The same issue, priced across your choice of agents and models.
Total cost per mission ($)*models.dev list prices, for one mission of about 1M input and 100K output tokens.
Cycle time (min)*Median wall-clock to a resolved, ready-for-human PR, from SHIP's own SWE-in-a-team benchmark research.
Budget
open-codeglm-5.2pideepseek-v4-flashclaude-codehaiku
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.
Planner
Claude Codeopus
Builder
glm
glmReviewer
Codexgpt
QA
Pikimi
PikimiZero-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
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
The operating system for agentic engineering, running on your terms.
Launch your agent fleet
Contact us for a demo with an expert.