PROOF
The proof
it actually works.
Honest technical evidence from public datasets. No customer stories. No marketing fluff. Each study below ran the same PAR pipeline on data anyone can audit, and surfaced a result no threshold system could.
Your SMEs already understand 80% of the matching work in your data backlog. Coherany lets them run it themselves. An LLM coach helps them define each pattern; the deterministic engine runs every decision in production, audit-ready by default. The studies below show what that looks like on real data.
Four days of warning before the Brooklyn blackout
52,636 Brooklyn electrical complaints. 254 patterns discovered, zero rules written. The outage-day Brownsville cell matched a named, human-approved insight at 90% similarity — and the signal was visible four days early.
We found doctors who bill like Medicare's banned ones
294,740 Medicare doctors grouped by billing behavior alone. No fraud labels. Four groups contained the already-banned doctors at up to 6.6× the baseline rate. 918 more doctors in those groups haven't been investigated yet.
Eight days of warning before the fire
Twenty weather stations. Seven years of public NOAA data. A pattern every threshold alert system missed, found without a single labeled example.
Anomalies were 3.3× more likely to be in critical state
NASA's most-cited predictive-maintenance benchmark, run through Coherany's pipeline with zero labels and zero custom code. The unknown patterns turned out to be where the failures live.
Nine patterns of praise across 270 cuisines
142,816 public Google Maps reviews, clustered with zero sentiment training. Nine cross-cuisine praise patterns emerged from the language alone, plus a complaint pattern that crosses 66 cuisines and an almost-there cohort a regional manager can act on tomorrow.
Your data is next.
If you have sensor telemetry, operational logs, or any stream of correlated signals — we can run the same pipeline on it. Request the methodology, or book a walkthrough and we'll run it on your dataset live.