Revelara reads the change you are about to ship and flags the reliability risks in it, with findings grounded in real incidents. It runs in the local dev loop before CI, so you fix the risk before it pages you.
Free 21-day trial. No credit card required.
In Claude Code, Cursor, or Copilot, or the rvl CLI, point Revelara at the change you are about to commit. No dashboard to set up.
Get reliability risks in your code, many of them tied to a real public production incident that shows the failure the pattern already caused.
Handle the risk in the local dev loop, before CI and before it becomes a page. Go deeper with correlated, cross-service, and systemic analysis when you need it.
Revelara connects your incidents, architecture, and team knowledge into a continuous reliability loop.
Install the CLI in 30 seconds. Revelara scans your codebase, maps risks, and delivers findings as slash commands right in your coding agent. No context switching, no dashboard to check.
/risks – See open risks for the current project/scan – Run a risk scan on your codebase/fix – Get remediation guidance for a specific risk/review – Review code changes for reliability risksRevelara matches your code against patterns from thousands of real-world incidents. Findings show their reasoning: what pattern was matched, what went wrong, and why it matters for your service.

Revelara continuously analyzes your reliability risks, classified by category, scored by severity, and linked to the services they affect. No more guessing what to prioritize.

Revelara turns risk findings into sprint-ready actions with embedded remediation controls. Approve, defer, or route to the right team, all from one place.

SOC 2's reliability controls live in engineering, not a compliance tool. Revelara maps them to the criteria they support and keeps the evidence current between audits.

Revelara installs into your coding agent over MCP, plus a CLI and editor plugins. Point any MCP client at the Revelara MCP server and it can research incidents, risks, and controls while it works.
Connect your issue tracking and bring in your own postmortems. Your incident history becomes org-specific signal, isolated to your tenant, so the analysis tunes to the failures your team actually hits.
Beyond code-time findings, Revelara gives an engineering leader a defensible reliability posture: 70 reliability controls, risk analysis, and compliance evidence, without hiring for a role that is hard to fill. It is coverage for a team that does not have a dedicated SRE, and it complements an SRE anywhere one already exists.

Posts on reliability work, the AI-generated code teams are shipping, and what the public postmortem corpus actually shows.
Install the Revelara CLI, point it at a codebase, and read your first ranked reliability risk register. About fifteen minutes end to end, walked on a real public repo you can clone and check.
We had an AI quality metric that was stable across model tiers, improved when we refined the system, and measured something tied to proprietary knowledge. Then we built a counterfeit with almost none of the relevant expertise and it scored 0.99. A metric is not trustworthy because the real system passes. It becomes trustworthy when the fake fails.
GitHub's February availability report documents two incidents an hour apart with the same root cause. The first mitigation was correct for what the team could see, and it was not the fix. This is a reading of the public report through two lenses, one heuristic and one systems-theoretic.
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We are careful with your code and transparent about how we handle it. See the security FAQ for exactly what Revelara reads, stores, and does not.
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