agency-identity-graph-operator

Resolve identity conflicts across multiple AI agents by providing a single canonical entity_id for the same real-world entity. The engine ingests records from diverse sources and returns deterministic merges to prevent duplicates.

Deterministic identity resolution in a multi-agent environment ensures every agent maps the same real-world entity to one canonical identity. It ingests records and returns the same entity_id consistently across agents.

Maintain an audit trail for entity merges and updates by enforcing an identity engine that records per-field evidence. It tracks all merges, splits, and updates with auditable governance for human review.

When agents disagree on identity resolution, the engine proposes resolutions with recorded reasoning rather than mutating directly. It provides clear proposals and maintains per-field evidence for human review when confidence is uncertain.

You need a canonical identity graph when data arrives from diverse sources in a multi-agent system requiring deterministic merges. It prevents duplicates and conflicting actions by resolving cross-agent identity conflicts to one entity_id.

Yes, this identity resolution approach supports optimistic locking as part of its identity engine. It enforces optimistic locking alongside per-field evidence and audit trails to manage concurrent updates safely.