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.
The difference
What makes the factory a factory
- 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
- 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
- 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
- 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
Before the factory
Qualified work enters the factory
Raw requests are evidence, not instructions. Coroid turns each signal into a sanitized, deduplicated, verified work item before an agent can act on it.
Passing requests promote automatically. Contradictory, low-confidence, unavailable-harness, and non-reproducible cases stop in an audited review queue.
The workflow begins with untrusted signals from manual requests, imports, reports, schedules, integrations, and monitoring. Coroid normalizes and sanitizes the input, checks whether the current release or canary already fixes it, deduplicates and clusters matching reports, performs type-aware verification or an isolated reproduction, and assesses impact, ownership, scope, difficulty, and confidence. Passing requests become a task, phased plan, report, or schedule. The implementation must then pass the same compiled Quality Graph at pull request, release, and canary checkpoints. Passing release evidence closes the original feedback. A matching future failure signature reopens it as a regression.
- 01
Raw signals
Manual requests, imports, reports, schedules, integrations, and monitoring enter as untrusted input.
- 02
Normalize and sanitize
Credential-like values are redacted and every tool remains constrained to the selected project.
- 03
Check the current release
A request that is already fixed on the latest release or canary closes with evidence.
- 04
Deduplicate and cluster
Exact identity, content fingerprints, and semantic confirmation join repeat signals to one issue.
- 05
Verify or reproduce
Type-aware checks or an isolated reproduction establish whether the requested outcome is real and feasible.
- 06
Assess and route
Impact, owner, scope, difficulty, confidence, and the right work type are recorded.
Create the right work
- Executable task
- Phased plan
- Evidence report
- Recurring schedule
Prove the outcome
Close feedback. Release evidence updates the originating system when its integration allows writes.
Reopen regressions. If the same failure signature returns, the issue cluster and its source feedback reopen automatically.
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.
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.
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 profilesUnder 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.