Autonomous security engineering that detects, explains and remediates vulnerabilities before they reach production.
A real CI failure. Watch the AST-aware remediation loop read the trace, name the cause, and open a Pull Request.
Every red build becomes a reviewed Pull Request through a transparent three-step workflow.
CI failures, vulnerabilities, and code quality issues caught the moment they hit your repository.
AI reads the logs, finds the root cause, and delivers a structured diagnosis with impact scope.
A scoped fix delivered as a PR, with the root cause written out beside it. Engineers review and merge. No autonomous commits, ever.
OmniSentient replaces active pipeline monitoring with Pull Requests that explain the failure and propose the fix.
AST-based engine corrects configuration drifts, dependency mismatches, and syntax errors — delivering terminal-ready fixes.
Structured PRs detailing why the build failed and how the proposed fix corrects it, so a reviewer can judge it without re-reading the trace.
A secure developer copilot in your PR threads. Request changes, ask architectural questions, or trigger re-runs in natural language.
Security-relevant records carry a SHA-256 hash binding each row to its predecessor, guaranteeing immutable, tamper-proof compliance logs.
No marketing fluff. Row-level security on tenant data, a scoped GitHub App rather than broad tokens, enforced retention windows, and an append-only audit ledger. Each one is enforced in code, and each one is described below as it actually works.
Indexing stores source chunks so your code can be searched and explained. Those chunks are deleted on a 12-month schedule enforced by a scheduled sweep, and deleting a repository removes its index immediately.
Row-level security is enabled on every tenant table, and writes are bound to an organisation id in the data layer itself. The code index is scoped per repository by a retriever that fails closed rather than falling back to an unscoped search.
Access is granted through a GitHub App installation scoped to the repositories you select, using short-lived installation tokens — not a personal access token carrying your whole account. Revoke it from GitHub at any time.
Sessions are managed via securely signed JWTs stored strictly as HttpOnly cookies to prevent token theft.
We are built for SREs and high-assurance engineering teams. Here are the facts.
No. Every autonomous write to your repository is made on a branch and proposed as a standard GitHub Pull Request — that is enforced in the write path itself, not left to policy. A human reviewer inspects, approves and merges. OmniSentient never writes to your default branch.
Diffs and logs are scrubbed for credentials before they are sent to any model, so secrets do not reach the AI layer. Files that carry configuration and secrets — .env, Dockerfile, docker-compose.yml, vercel.json — are on a block list the remediation engine will not write to. Every write is additionally path-checked and size-limited.
No. The AST-based analyser walks the syntax tree and sends only the isolated failure context to the model, not whole files. On top of that, AI tokens are a metered quota enforced per plan — the Free tier stops at 500,000 tokens a month. The ceiling is a hard limit, not an estimate.
Connect your repository and watch OmniSentient diagnose your first failure, explain the cause, and open a Pull Request with the fix. No install. No card. Revoke anytime.
Free tier active. 500,000 AI tokens and 100 background jobs a month included.
Read-only by default. No card. Revoke anytime.
