Customer issues
A refund that never arrived or a wrong invoice usually lives in the data and the code. TraceX follows it there.
Many monitoring and logging platforms now include an AI assistant. Here's how that differs from TraceX, and why teams use both.
| What matters | TraceX | Monitoring assistants |
|---|---|---|
| Where it starts | A customer report, a ticket, an alert or a question. | Usually an alert, a dashboard or a query inside that platform. |
| What it reads | Your database, code, logs, errors and support tools together. | Mainly the telemetry stored in that platform. |
| Questions about data | Answers from production data, such as “which refunds are stuck?” | Built for metrics, traces and logs rather than business records. |
| The result | A root cause with cited evidence, a fix as a pull request, and a customer reply. | Explanations and summaries of the telemetry. |
| Who uses it | Support, engineering, and anyone who asks in plain English. | Mostly the engineers who work in that platform. |
A refund that never arrived or a wrong invoice usually lives in the data and the code. TraceX follows it there.
One investigation reads the database, the repository and the logs, instead of one tool at a time.
It ends with a fix to review and a reply to send, not only an explanation.
TraceX reads from monitoring tools such as Sentry, Datadog and CloudWatch. Keep your monitoring and its assistant for system health, and let TraceX take customer issues to the root cause across your data and code.
No, but it uses it when connected: errors and logs often show when a problem started.
No. TraceX reads what an investigation needs, read-only, when it needs it.
See Integrations for the current list.
More comparisons: all comparisons · choosing an AI root cause analysis tool · TraceX and monitoring assistants · TraceX and investigating by hand
TraceX is free during the private beta. Connect a database and a repository and ask your first question in minutes.
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