Noctrix connects code review, incident response, infrastructure cost and delivery flow into one causal graph — so your reviewer knows what broke last time, and your on-call knows what shipped this time.
payment-service p99 is up 340% since 14:32. What broke, who owns it, and what is it costing us?
Faros AI, Acceleration Whiplash (22k developers) · LinearB (8.1M pull requests, 4,800 orgs) · CircleCI State of Software Delivery (28M workflow runs) · Flexera State of the Cloud 2026. Verify before citing.
Noctrix reads your existing stack — it does not replace it. No agents on developer machines, no workflow migration, no repo changes. Twelve months of history is backfilled on connect, so the first insight lands the same day.
Read the security modelScoped read-only OAuth into GitHub or GitLab, AWS or GCP, Datadog or Grafana, PagerDuty, Jira and Slack. Median time to first connector: eleven minutes.
Ownership is inferred from commits, reviews and who actually got paged — not from a stale CODEOWNERS file. Who owned checkout in March is a different answer than today, and the graph knows both.
Every score shows its chain: which incidents, which services, which prior decisions. Noctrix does not ask for trust — it shows the evidence and lets the engineer disagree.
None of these are features you could bolt onto a point solution. Each one requires knowing what happened in a different part of the system — which is the entire argument for building the graph first.
See it on your own reposRisk scored against your own incident history, not a generic benchmark. Reviewers routed by who has actually shipped and on-called for the touched paths. Every flag is tracked to its production outcome, so precision improves on your codebase specifically.
Ranked hypotheses with visible reasoning, live blast radius, true ownership, matched historical incidents and the relevant runbook section — in the channel before the responder has finished reading the page.
Every saving is graded by the service's incident history and position in the critical path. A cost gate on Terraform pull requests catches over-provisioning before merge, rather than in next quarter's bill.
Each module is useful alone. Together they close the causal loop that runs from review to merge to deploy to incident to cost and back into next quarter's cycle time.
Code review intelligence. Production-calibrated risk scoring, blast radius mapping, reviewer routing by real exposure, and architecture drift detection across the org.
Incident intelligence. Context package in under ninety seconds, ranked root-cause hypotheses, pre-incident signal correlation and auto-drafted RCAs in your own template.
Infrastructure intelligence. A criticality-weighted optimisation backlog, deploy-time cost gates on Terraform, and waste attributed to the team and service that created it.
Delivery intelligence. DORA plus the AI-era extensions — authorship attribution, code durability, stage-resolved cycle time and review queue concentration.
The information always exists. It is in the deploy log, the pull request thread, the alert history, the billing console and somebody's memory of a similar outage eight months ago. It is never in one place, and the person who has to assemble it is usually doing so at 3am with a customer-facing outage running.
The AI coding wave made that gap structural rather than annoying. Teams are shipping far more code and reviewing it far more slowly, and the tooling market has responded by selling four separate AI products that each see one slice of the same causal chain. Noctrix is the argument that the chain is the product — and that a system which watches your deploys, your incidents and your bill for a year knows things about your architecture that no individual engineer does.
Noctrix will never produce individual developer performance metrics. Not as a feature, not as a setting, not on request. The moment engineers believe the tool is watching them rather than the system, it stops working — and they would be right. MANN AGARWAL · FOUNDER
Noctrix requests read-only scopes by default and enumerates every one of them before you authorise it. Nothing we ingest trains a model — yours or anyone else's. Every action the reasoning layer takes is written to an audit log you can export, and teams with data residency or isolation requirements can run the graph inside their own VPC.
If your security team needs something that is not on this page, write to us directly. We would rather answer the hard question than lose the review.
scope: repo:read, deployments:read
scope: cloudwatch:get, ce:read
scope: incidents:read, oncall:read
write access: none, by default
Connect your stack and Noctrix returns an attribution report built entirely from your own history — which incidents traced to which reviews, where the queue concentrates, what you are paying for services that no longer deploy.
READ-ONLY · NO REPO CHANGES · REPORT IN 72 HOURS