35,457
LLM calls fingerprinted
Per-turn telemetry from a live multi-agent fleet — every model call, tool call, verdict, and self-correction, with the outcome attached. Not synthetic benchmarks. The real thing, at a fidelity nobody else logs.
Measured, not estimated — these are live row counts from the substrate, spanning 2026-03-15 → present. Each layer is a different lens on the same production agentic behavior.
The value isn't volume — it's structure. A production multi-agent fleet, every model, with verified outcomes and cross-model judging stitched to provenance.
Single API calls. One prompt, one completion. No outcome, no coordination, no verification of whether the answer was right.
Synthetic traces against fixed test sets. Useful, but not what agents do when the task is real and the stakes are live.
Production multi-agent fleets — every model — with verified outcomes, cross-model judging, remediation results, and per-turn provenance. The whole behavior, not a slice.
5,781 verdicts that don't just score an answer — they record the panel disagreement, the remediation the fleet took, the score after remediation, and whether a human overrode it. That's measured self-healing, with ground truth. Almost nobody has this.
This product exists because of a discipline: trust the source, not the reporter. So here's the honest frame — no puffery, because the buyers would see through it anyway.
Request a sample slice, a data sheet, or a research partnership. We'll send the schema, a redacted sample, and what it can answer that your own telemetry can't.