CoroidYour AI software factory

Why Coroid

Your AI software factory, from task to pull request.

You define the work. Coroid coordinates specialized AI agents to plan, build, test, and review it in the cloud, with quality checks and approval rules at each stage. The result is a verified pull request for your team to approve.

Start FreeBook a demo

The difference

What makes the factory a factory

  1. 01

    Autonomous delivery, with your oversight

    Once you specify a task, Coroid plans, builds, tests, and reviews the work. Agents follow your quality checks and approval rules, then return a verified pull request with evidence you can inspect.

    • Specification in, verified pull request out
    • Specialised architecture, build, QA and review agents
    • You set the approval rules and review the outcome
  2. 02

    Nothing to run, nothing to manage

    Coroid is cloud-based end to end. No IDE plugin, no terminal session to keep alive, no agent to supervise. The harness provisions an isolated workspace per task, orchestrates every agent and cleans up after itself.

    • No sessions, no context windows to nurse
    • Isolated cloud workspace per task
    • Work continues without an active coding session
  3. 03

    One agent or a thousand, in harmony

    Throw one task or a thousand at the factory. The harness analyses dependencies across your repositories, sequences the work in the right order and resolves conflicts before they reach a branch — so parallel agents compound output instead of colliding.

    • Dependency analysis across monorepos and polyrepos
    • Conflict resolution built into the harness
    • Throughput scales with agent slots, not headcount
  4. 04

    One quality graph gates everything

    Your checks live in a single compiled quality graph — goals, expectations, evidence. The same graph gates a manual run, a task on the line, and a pull request on GitHub, and it returns one decision: go ahead, or redo — with the cause and the owner attached.

    • Same graph for manual checks, task QA, and pull requests
    • Evidence is locked to the exact commit — stale results cannot pass
    • No one can hand-write a pass — verdicts come from executed checks only

Inside the factory

Every task runs the same production line

Six stations, each with a gate the work must pass before it moves on. The same disciplined sequence runs whether the factory is handling one task or a thousand.

A failed gate never reaches you. The task routes back, gets reworked and runs the line again — you only see work that passed. And every gate comes from one compiled quality graph, so a manual check, a task, and a pull request are held to exactly the same standard.

A ladder of the six stations every task passes through: specification, architect, developer, QA, reviewer, and pull request. A gate sits between each pair and stays shut until the station above it signs off, so work only descends once it has passed. The diagram loops through a task making that descent.

The honest trade-off

Quality costs tokens. That is the point.

A factory task spends roughly two to three times the tokens of a vibe-coding session in Claude Code, Codex or Gemini CLI — because separate agents plan, test and review the work before it reaches you. You are buying consistency, not keystrokes.

Tokens per task
2–3×
Quality gates
Enforced at every station
Output consistency
Repeatable and auditable
Your role
Approve the outcome

Token spend per equivalent task, relative to a single-agent CLI session.

Prefer raw speed over ceremony? The Ludicrous profile relaxes the gates and matches CLI-level token spend. It is there when you need it — it is just not why Coroid exists.

Explore AI profiles

Under the bonnet

Everything else the harness takes care of

Specification-first intake
Goals, business value, user stories and acceptance criteria — agents validate against the spec, not guesses.
Review evidence orchestration
Previews, scans, coverage and external AI reviews from Vercel, Netlify, CodeRabbit, Codecov, Snyk and more attach to every pull request.
Progressive skill system
Agents load specialised expertise on demand, keeping context focused and token use efficient.
MCP and event hooks
Connect Sentry, Jira, Slack and your own tools, and automate reactions to platform events without code.
GitHub and GitLab native
Public, private and enterprise repositories with scoped, encrypted credentials.
Autonomous remediation
Infrastructure issues are classified and fixed in-task, or spawn dedicated remediation work.
EU hosted, on-prem ready
European hosting with a full GDPR posture, or run the factory on infrastructure you govern.
Transparent pricing
Provider token rates passed through with zero markup. You see every part of the bill.

The factory ships. You approve.

Connect a repository, specify the work and let the factory run. Your first verified pull request is one task away.

Start FreeBook a demo