For AI agents: a machine-readable documentation index for this API is available at /llms.txt. Every page is also available as Markdown — append ".md" to the URL or send an "Accept: text/markdown" request header.

Find customers about to churn on errors

Surface the end-users whose error rate is climbing, then read what is failing for them.

Aggregate error rates hide the customers who are actually having a bad time. This finds the end-users whose failure rate stands out, then reads their traffic so you can tell a broken integration from a broken endpoint.

Reach for this on a regular sweep, or before a renewal conversation, when you want the list of accounts worth contacting and a specific reason for each one.

Steps

Restless runs these six in order with your stored key. Nothing here changes data.
  1. 1

    Confirm the identity and access behind the API key with GET /api/v1/me.

  2. 2

    Pick the target project. If you only have an example slug, verify it with GET /api/v1/projects/{slug}, or browse options via GET /api/v1/projects.

  3. 3

    List the users whose error rate is above the line with GET /api/v1/projects/{slug}/users, passing atRisk=true. Tune threshold (a percentage) and minRequests so a user with two total requests does not outrank a heavy user sitting at 30 percent.

  4. 4

    For each user worth chasing, pull their recent failures with GET /api/v1/projects/{slug}/logs, passing their address as groupEmail and narrowing with status.

  5. 5

    Open the clearest example with GET /api/v1/projects/{slug}/logs/{logId} and work out whether the fault is theirs (a malformed request, the wrong credential) or yours.

  6. 6

    Report back per user: what they are calling, what is failing, and which of those two it is.