One Slack message.
What broke, what changed, who owns it.
Clarix sits between your existing tools and your on-call engineer. It correlates deploy events, runtime errors, and logs — and posts a structured incident brief to Slack before anyone has opened a dashboard.
payment-service error spike — 3 min after deploy v2.4.1
ConnectionRefusedError: db-primary:5432Example alert — generated from real signal data, not a template
Why Clarix
Vendor and tool agnostic
Works with whatever observability stack you already have — Datadog, CloudWatch, Prometheus, or nothing. No lock-in, no rip-and-replace.
Works with immature observability
Most tools require a mature setup before delivering value. Clarix surfaces what context is missing and tells you exactly what to instrument next.
Signal health dashboard
Know before an incident exposes it. Clarix detects stale log ingestion and silent signal gaps, so you find out before your users do.
Noise classification
Not every error spike is an incident. Clarix learns your patterns per org and filters inactionable noise — with a human feedback loop that improves it over time.
How it works
Connect in an hour
Add a GitHub webhook, drop an OTel Collector config into your cluster, paste a Slack webhook URL. No agent to operate.
Clarix watches your signals
Deploy events, pod restarts, crash loops, error log spikes — correlated across services, not reported in isolation.
One Slack message
When something breaks, your on-call gets context in seconds — not three dashboards and a fifteen-minute archaeology session.
Want early access?
We are running a small pilot with engineering teams who want faster incident context. Drop your email and we will reach out.