Ship

Ship is a platform that treats AI coding agents as a managed engineering team rather than a loose collection of copilots. It assigns work to specialist agents that handle planning, building, reviewing, deploying, and testing, then tracks what each one costs and ships. The goal is to let you run autonomous software delivery without giving up visibility or control over the process.

The problem it tackles is a common one for teams adopting AI coding tools. You can spin up agents that write code, but coordinating them, verifying their output, and understanding what you're actually spending is left to you. Ship puts structure around that by treating each unit of work as a mission and routing it through agents with defined roles, so you always know where things stand and what they cost.

Under the hood the platform runs six specialist agents. A Researcher gathers context, a Planner breaks down the work, a Builder writes the code, a Reviewer checks it, an Operator handles deployment, and a Tester runs verification. You watch progress in a Mission Control dashboard that shows inference cost per step, model used, and outcome. Pull requests come out gated, meaning they don't merge until reviews and tests pass.

It's built for development teams that want the output speed of AI agents but need the accountability of a real delivery pipeline. If you've tried pointing Claude or GPT at a repo and found the results hard to trust at scale, this is the layer that's supposed to close that gap. The platform plugs into GitHub and Linear and lets you route work through OpenAI, Claude Code, or OpenRouter, so you pick which models run which roles.

Security is handled with zero-trust design. Credentials stay encrypted, agents run in isolated sandboxes, and you can deploy the whole thing on your own infrastructure and region if compliance requires it. That makes it a fit for teams that can't ship code through third-party systems without audit trails.

Pricing isn't published as a flat rate. Instead, you pay per mission at inference cost, with the dashboard showing what each run actually costs. Examples on the site range from a few cents to a couple of dollars per mission depending on scope and model. If you want to see it in action before committing, there's a demo booking flow on the site.