Entity Coherence in enterprise AI: the missing layer
The most common failure mode in enterprise AI is not hallucination from the model. It is inconsistency in the data the model retrieves.
What is Entity Coherence?
Entity Coherence is the property whereby every person, company, deal, document, or concept is understood as a single consistent identity across all agents, systems, and sessions — maintained at ingest, not resolved at query time.
What happens without Entity Coherence
Contradictory agent outputs, hallucinated identity, duplicated records, and unreliable audit trails are predictable failures without coherence at ingest.
Maintaining Entity Coherence at scale
Cross-source identity resolution, confidence-weighted identity, temporal identity management, and conflict handling — all at ingest.
Frequently asked questions
What is the difference between Entity Coherence and entity resolution?
Entity resolution merges duplicates retrospectively. Entity Coherence is a continuous architectural property maintained at ingest.
Why does Entity Coherence matter for multi-agent AI systems?
Without it, each agent builds its own understanding of each entity. With it, every agent works from the same coherent entity.
Can Entity Coherence apply to non-person entities?
Yes — companies, products, deals, documents, and any concept that appears under multiple names across sources.
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