Coharyn Assure
Continuously prove that the data still makes sense.
Once Coharyn has learned and validated how a system should behave, it compiles that knowledge into deterministic checks that run on a schedule — surfacing inconsistencies as they emerge, with evidence.
- Broken relationships and orphan records
- Impossible or contradictory states
- Distribution and schema drift
- Unusual distributions and missingness
- Timing and freshness deviations
- Emerging cross-system inconsistencies
Coharyn learns the unknown, proves what it learns, and executes the known efficiently.
Compiled deterministic checks run without continuous model inference. In controlled validation, steady-state assurance executed with no LLM calls — the platform's north-star metric is its LLM-free execution ratio.
Tested before it runs
Every compiled check ships with generated positive and negative tests; a check reaches the schedule only after its own tests pass.
Severity and health
Findings carry severity and roll up into a transparent health signal with full evidence drill-down — never an opaque score.
Drift-aware
When distributions or schemas shift materially, affected knowledge is reopened and revalidated rather than silently trusted.
Explainable
Each anomaly states the expected baseline, the observed value, the affected dimensions and the likely related change.
Start with a private pilot.
Connect Coharyn read-only to one unfamiliar system, or several. See what it discovers, with evidence, before you commit to anything.