Self-Maintaining

HASH continuously compares your entities, relationships, and types against the rules that define your domain. Impossible states, missing required facts, and conflicting values are flagged before they quietly spread through your graph.

New claims are checked against connected systems, uploaded documents, and prior context from ingested sources. HASH keeps the supporting evidence attached, so each fact can carry a confidence signal and a clear explanation of where it came from.

Agents can revisit low-confidence facts, request additional evidence, propose corrections, or escalate to a human reviewer. Every check and suggested fix is recorded with full provenance.

As your graph changes, HASH reruns checks that catch stale assumptions, process deviations, and unusual changes in the world it represents. The result is a knowledge graph that becomes more trustworthy as it grows, not more fragile.