§ Arkheia · Social Proof
151 agents.
5 months.
Zero defects.
The story of scaling an autonomous agent fleet from 12 to 151 under continuous governance — with zero hallucination-caused outages.
§ Key Learnings
What made it work
Per-model behavioural profiles
Generic thresholds fail at scale. Each model family was profiled independently from empirical characterisation data.
Three-zone classification
Admitting uncertainty (Yellow zone) prevented the false confidence that causes silent failures in binary systems.
Kill-switch propagation
When a model showed drift, a scoped kill-switch disabled it across 151 agents in under a second. No manual intervention per-agent.
Continuous certification
Every agent was compared against its golden image configuration continuously. Drift triggered re-certification, not silent degradation.
The Empirical Claim
“5 months building with a multi-agent process: zero hallucination-caused defects. All failures were scope or infrastructure. Arkheia ate its own cooking.”
This is not a theoretical claim. This is production data from an organization running 151 agents under continuous Arkheia governance.
Want these results
for your fleet?
Start with the detection engine. Scale to full governance. See the difference in your first week.