Failed runs don't just waste compute - they waste your team's time and delay every deploy. See the full cost of CI failures across all your pipelines.
Currently onboarding a small group of DevOps teams. Direct access to the founder.
See real compute cost, not just wall-clock time that hides the true bill
Every failed run burns compute and blocks your team from shipping
Track how CI reliability and speed change over time
Find the branches, jobs, and contributors causing the most re-work
Every failed run is a developer waiting, a deploy delayed, and money wasted. See exactly where the bottlenecks are.
Success rates, failure patterns, and compute costs per pipeline. Know which pipelines slow your team down and which ones just work.
Find the jobs that fail the most, take the longest, and block the rest of the pipeline. Fix the bottleneck, unblock the team.
Know immediately when a pipeline breaks or slows down, before your team sits idle waiting for a build that already failed.
Ranked risk scores surface the branches, jobs, and patterns causing the most failures and re-work. Fix what matters first, ship sooner.
Organize your team with role-based access control. Share insights and collaborate on pipeline optimization.
Your data is encrypted and secure. Row-level security ensures organizations can only access their own data.
You can. AI agents make building an internal dashboard fast. But there are a few things that take longer than an afternoon.
When you run 6 parallel jobs, GitHub bills 30 minutes for a 5-minute run. Most internal dashboards track wall-clock time and miss the real cost entirely. Getting this right across providers, edge cases, and job exclusion logic took months of iteration.
A polling-based solution hits CI provider API rate limits fast when you have 10+ repos. RunWatch uses a push model - one lightweight step at the end of your workflow, no tokens to rotate, no rate limits, no cron jobs to babysit.
An AI agent can scaffold a dashboard in a day. But schema migrations, provider API changes, alert dedup edge cases, and multi-tenant access control are ongoing work. At engineering rates, 2 hours of maintenance per month already costs more than a Pro plan.
GitHub Actions and GitLab CI today, with more providers coming. Status normalization, inline vs. external mode detection, and job-level compute are handled per provider. One dashboard, every pipeline.
Still want to build your own? Check out our blog for the formulas and methodology we use. We publish what we know.
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See the real cost of CI failures - in compute, developer time, and delayed deploys. Free to start, no credit card required.