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AI coding that can’t fake done.
CrewWork plans, writes, and validates changes on a single local 27B open-weight model. Done is decided by tests the platform ran itself in an isolated sandbox, never by the model’s own report. Nothing merges without you.
Self-hosted. Runs on Qwen3.8 27B today, or any OpenAI-compatible endpoint. No frontier API and no per-seat fees. Every change lands on an isolated branch for your review.
Platform overview
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Every claim of success is checked by code the model cannot touch
Language models report success optimistically. CrewWork is built on the opposite assumption: a completion is earned with evidence the platform produced itself, in isolation, and everything that enforces it fails closed.
Provenance is stamped, not trusted
Every verification check is tagged at one splice point as platform-sourced or model-sourced. The tag is written last, so a model cannot forge it, and only platform-sourced checks count toward completion.
Evidence works in both directions
A model that reports done while platform evidence is failing is overridden to failed. A model that reports failure while the evidence is clean is sent back to repair. Neither claim is accepted on its own.
Missing evidence means no
If the validator did not run, a step cannot complete on the model’s verdict. A program that reaches its end without the enforced validation floor is marked failed, never quietly finished.
Autonomous, auditable, reversible
- Isolated environments. Each run executes inside a kernel-isolated gVisor sandbox with its own copy of your code and hard caps on CPU, memory, and processes. Failed attempts are discarded with their worktree; your repository is never touched.
- Review-gated output. Changes land on isolated local delivery branches with diffs, logs, and validation summaries attached. Platform self-repair changes land as draft PRs. You decide what merges.
- Execution limits. Configurable caps on token spend, iterations, and wall-clock time per run, plus per-step allowed-path scoping and daily repair budgets.
- Audit trail. An append-only workflow event log, durable run artifacts, and checkpoint state are inspectable and resumable.
Project-scoped compliance evidence reports package that history into PCI DSS-oriented and OWASP ASVS-oriented views: organized evidence, not a certification.
Safety and trust
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The platform runs this loop on its own codebase. A Platform Self-Repair program on Qwen3.8 27B goes from plan through isolated validation, review, and the promotion matrix to a draft pull request on the platform repository that a person reviews and merges.
Stop managing tasks. Start shipping initiatives.
Describe an initiative as a program charter. Infinite Coder turns it into one coherent feature slice with a single implementation step, executes it in one continuous session, and runs a whole-program review at the end. Automatic scheduling keeps long-running work moving.
See the full Infinite Coder feature- One coherent feature slice and a single implementation step per charter, so the engine can finish in one continuous session
- Deterministic validation at every checkpoint, with repair inside the run
- One whole-program semantic review at the end, not a review after every turn
- Structured, replayable records for auditable progress
- A plan-approval step before execution starts on your own programs
- Prompts grounded in your actual codebase structure
- Runs seeded directly from action items, synced issues, and AI suggestions
What comes after error monitoring
CrewWork ships with Sentry-powered error monitoring that feeds directly into the remediation pipeline. Runtime and preview errors are captured and grouped by pattern. When thresholds are met, validated fixes are generated in isolated environments, run through your build, lint, and test commands, and land on isolated local delivery branches for you to inspect.
See the full HotFix flowHotFix pipeline
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Built to run unattended
Autonomous systems earn trust through predictability. Runs persist through service restarts, budgets stay bounded, and event-driven updates keep every change visible the moment it happens.
- Real-time activity timeline keeps your team synchronized via event-streamed updates
- Runs survive browser or service restarts with Postgres-backed durable state
- Workspace locks prevent runtime jobs from stepping on each other, so automation never conflicts
- Repeated identical failures are stopped automatically after 3 consecutive occurrences by default, and the count is tracked durably so a crash or restart cannot reset it
- Every change is reversible and auditable through Git checkpoints and artifacts
- Validated builds can ship to other hosts on your own network through an outbound-only, mutual-TLS release agent, with on-call rotations that escalate automatically when a deployment fails
- Only actionable recommendations reach you, because suggestion output is evidence-based and filtered through an automated review pass
Reliable execution and controls
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One 27B model. Your hardware. Your data.
CrewWork’s validated default is a single Qwen3.8 27B open-weight model serving every lane: planning, implementation, review, structured extraction, and chat. It runs on your own hardware and sends nothing anywhere unless you opt in. Point it at any OpenAI-compatible endpoint if you prefer.
A 27B model is reliable here because the platform does not ask it to be trusted. Structured output is schema-validated and rejected when it does not conform. Prompts are compiled from a typed context graph of your repository under a fixed budget. Placeholder and stub code is rejected with automatic retry. The model writes. The platform decides.
Read the technical white paper- A typed context graph of your repository, service topology, tests, API contracts, and run history, rebuilt only when code or task state changes
- Two-stage structured extraction: natural-language analysis first, then schema-validated typed output that is rejected, not coerced, when it does not conform
- Extended reasoning switched on per lane, and only where the model registry says the model supports it
- Cost and latency traced on every model call, with per-invocation cost visibility, and raw prompts and outputs never stored
- Every delivery branch validated against your build, lint, and test pipeline before it reaches review
Three steps take you from connected repo to reviewed change
Connect your code, define what you want built, and let CrewWork execute with built-in checkpoints and review.
01
Connect
Connect repositories from GitHub, GitLab.com, or Bitbucket Cloud, or start with a local project. CrewWork clones and indexes your code.
02
Define Work
Define a program charter for what you want built, launch delivery-planned programs, or start individual work directly from the workbench surfaces.
03
Run & Review
CrewWork executes with persistent state, automatic checkpoints, and built-in review gates. Larger initiatives run as delivery-planned programs: one coherent slice, one implementation step, and one whole-program review at the end. Runtime errors flow into HotFix, and every delivery branch and PR can be tracked through Runs and Source Control.
Workflow timeline
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Proof, not promises
See exactly how CrewWork keeps a model honest, explore the architecture, or reach out to talk it through.
Or view the architecture for the full technical picture.