Launching today
Traceroot is an AI-native, open-source observability tool that connects logs, traces, metrics, code, and team discussions. It doesn’t just summarize issues — it helps fix them by creating GitHub issues and PRs in a developer-friendly workflow.
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TraceRoot.AI
Hey Product Hunt 👋
I’m Xinwei, co-founder of @TraceRoot.AI
We started TraceRoot after facing the same problem again and again - fixing production bugs is slow, painful, and scattered across too many tools. Engineers jump between logs, traces, GitHub, Slack, and dashboards just to piece together what happened.
TraceRoot is an open-source debugging platform with AI agents that actually do the work: they pull together logs, traces, code, and related context into one place, explain the problem, and link every insight back to the original data so you can trust it. The agent can even draft fixes or open pull requests for common issues - you stay in control, it just handles the grunt work.
Unlike other tools:
- We organize all your telemetry data in a centralized platform optimized for debugging experience.
- Connect to all your engineering contexts and use context engineering optimization to improve the agent performance and directly create github PR and issues from our tool.
- Keeps track of all your past bug fixes for future reference.
Would love your feedback. You can register at traceroot.ai and integrate TraceRoot with your system by using our SDK. Checkout our Github for self-hosting option.
Thanks for taking a look.
- Xinwei
PopPop AI Vocal Remover
Great tool and I will share it with our developers, haha
TraceRoot.AI
@charlenechen_123 Thanks! That's our mission to make developers' life easier 😄
Just tried the demo—love how TraceRoot links logs straight to GitHub issues. I’ve lost hours hopping tools… this feels like an actual teammate. Curious: how well does it scale?
TraceRoot.AI
@cyrusandrew Thanks! Yes that's our mission! Our production is built upon some cloud services so that it should be scalable enough to handle most cases.
TraceRoot.AI
@cyrusandrew Thanks for trying it out 🙌 Glad the GitHub linking feels useful!
On scaling:
Microservices: The SDK is a lightweight wrapper around OpenTelemetry, so it scales naturally across distributed services.
Telemetry volume: It handles a good amount today, and we’re continuously working on strengthening the infra as usage grows.
We're keeping scalability top of mind as more teams come on board these days.