Free on your hardware. Metered on ours.

When an eligible check fails, Hive attaches the run, logs, diff and failing tests to a scoped AI-agent task. The agent writes a candidate; the wrapper applies its configured verifier and pushes the result to your branch. A fresh CI run on that branch decides whether the candidate worked, and your normal review and merge policy stays in charge.

Model requests go only to the provider you configure, using your own credentials. On runners you connect, the checkout stays on that hardware. A local check snapshot or hosted workflow can temporarily store source, logs or artifacts under the published retention policy; Hive does not use your source to train a model.

Hive is operated by Pulsar-Projekte GmbH, a German company registered in Bavaria. The control plane runs on a server in Germany; this marketing site is delivered as static files by Cloudflare. There is no analytics, no tracking and no cookie banner here — the Datenschutzerklärung sets out exactly what is processed and on what legal basis.

You bring your own model API key, so token costs go straight to your provider at their rates — no markup. Hive shows per-fix token spend and lets you set hard daily caps, so there are no surprise bills.

No — but you can use it, and it is free if you do. We host the control plane and the UI; you choose where the work runs. Connect your own machines as runners with a one-line install (Linux, macOS, Windows), rent capacity from us as booster packs, or mix the two and let the queue spill over onto ours when yours is full.

Yes. An agent launched onto your workstation gets a real git worktree there and uses that machine’s checkout, toolchain and explicitly allowed caches. Source stays on the workstation for that lane. A cloud session instead uses an ephemeral checkout on rented capacity; both appear in the same browser workspace, with controls that match each lane’s trust boundary.

Compute you rent from us by the minute instead of buying. When a run uses hosted capacity, Hive records the settled CPU-milliseconds against the tenant and project so you can see what each run spent and what balance remains. Private-beta tenants get 50,000 CPU-minutes a month. Packs are denominated in compute rather than money, so a repricing changes what a new pack costs and never what you already hold. Balance-based admission enforcement is still rolling out during the beta.

No. A repo opts in by committing one file, and Hive starts in shadow mode — it posts its own status and requires nothing, so your existing pipeline keeps gating merges exactly as before. You compare the two on real commits for as long as you like. Making Hive a required check is a separate decision you make in your repo settings, and our own onboarding runbook tells you not to retire the old CI until a preflight check reports clean. Start with one repo, one job — a useful pipeline is a few lines — and widen it when it has earned that.

No — it runs them. Hive’s agents authenticate as you, with the subscription or key you already pay for: an Anthropic Claude or OpenAI Codex subscription, a Cursor account, or an OpenRouter key routing to whatever model you like. Your local setup is untouched, because CI runs server-side and needs nothing installed on your machine. And Hive exposes over a hundred MCP tools, so you can drive runs, read logs and diagnose failures from the editor and agent you already use instead of switching to our UI.

No. Hive reads code, posts statuses and receives webhooks through a GitHub App, so today it runs GitHub repositories only. There is no GitLab or Bitbucket integration, and we are not announcing one here.

A failed lint, test or build step whose pipeline opted in with on_failure. Infrastructure failures and timeouts never wake a fixer, a fixer’s own commit never wakes another one, and a fixer that fails or cannot verify its work leaves the original failure standing. The candidate must pass a fresh CI run and it never merges by itself — your review and merge policy remains authoritative.

A Starlark file at .hive/main.star. A useful one is a few lines: load the standard pipeline builder, name a lint step and a test step, and optionally attach a fixer to the test step. The docs page “Your first pipeline” shows the shape and how to watch the first run.

hive check --step <name> uploads a snapshot of your working tree, runs that step and its dependencies on the fleet, and prints the failing task’s log tail. It needs a reachable server, a token and a registered project; it is not a local runner.

Runs 90 days, events 14 days, artifacts 7 days, caches 30 days; a hive check snapshot is deleted after 7 days. Deletion from object storage is carried out transactionally rather than by a best-effort sweep.

Actions runs your workflow and hands you a red X. Hive runs your pipeline and hands you a fix. Beyond the factory, you get pipelines as real code (Starlark, not YAML), warm caches by default, and the choice of whose hardware the work runs on — yours at no compute cost, ours by the minute, or both.

Hive is in private beta now. Waitlist members are invited in order and get early-bird terms; every beta tenant gets 50,000 CPU-minutes a month to run jobs on our hardware while they try it — about 12× GitHub Actions’ free tier.