We're thrilled to announce that Deeptrace is officially launching as part of Y Combinator's W26 batch. After months of working closely with engineering teams, we've built what we believe is the future of incident response — an AI SRE agent that can root-cause your engineering alerts in seconds, not hours.
The problem
Every engineering team knows the pain. An alert fires at 3 AM. An on-call engineer wakes up, groggy and disoriented, and begins the tedious process of:
- Checking dashboards
- Tailing logs
- Correlating metrics
- Searching through recent deploys
- Asking teammates for context
This process takes 45 minutes on average — and that's for experienced engineers who know the system well. For newer team members, it can take hours.
"We were spending 30% of our engineering time just investigating alerts, most of which turned out to be the same recurring issues." — Staff Engineer at a Series C startup
How Deeptrace works
Deeptrace connects to your existing observability stack and watches your alerts in real time. When an alert fires, it automatically:
- Analyzes logs with semantic understanding, not just keyword matching
- Traces through your code to identify the root cause
- Correlates across services to find upstream dependencies
- Generates a root cause analysis with suggested fixes
A quick example
Here's what a typical Deeptrace investigation looks like:
alert: HTTP 500 spike on /api/checkout
service: payment-service
root_cause: Database connection pool exhausted
→ Caused by: Long-running transaction in OrderService.processRefund()
→ Triggered by: Deploy #4521 (2 hours ago)
suggested_fix: |
Increase connection pool size from 10 to 25 in config/database.yml
Consider adding a timeout to OrderService.processRefund()
confidence: 0.94
In this case, Deeptrace identified the root cause in 12 seconds — something that would have taken a human engineer 30+ minutes to piece together.
What makes us different
There are other tools in the AIOps space, but Deeptrace takes a fundamentally different approach:
| Feature | Traditional AIOps | Deeptrace |
|---|---|---|
| Analysis method | Pattern matching | Semantic reasoning |
| Code awareness | None | Full codebase understanding |
| Time to root cause | Minutes to hours | Seconds |
| False positive rate | 30-40% | Under 5% |
What's next
We're just getting started. In the coming months, we'll be rolling out:
- Auto-remediation — Deeptrace will be able to apply fixes automatically for known issue patterns
- Predictive alerts — Catch issues before they become incidents
- Team knowledge graph — Learn from your team's past investigations
If you're an engineering team tired of the alert fatigue, we'd love to chat. Book a demo and see Deeptrace in action.
Deeptrace is backed by Y Combinator and is currently available in early access. We're working with teams of all sizes, from startups to enterprises.