agency-identity-graph-operator

Identity resolution across multiple agents requires a centralized graph that ingests records from various sources and produces stable canonical entity_ids. This ensures every agent shares a single source of truth, preventing duplicates and conflicting actions through deterministic matching.

Deterministic identity resolution handles merges and splits by relying on per-field evidence and versioned events. This approach maintains an auditable decision history, ensuring that when entities are combined or separated, the changes are tracked with supporting evidence for data integrity.

Identity resolution supports multi-tenant systems by scoping queries to specific tenants and applying PII masking to sensitive fields. This ensures tenant isolation while maintaining data integrity, allowing multiple tenants to use the shared identity graph without exposing protected information.

Maintaining data integrity when agents encounter the same entity requires evidence-driven matching against a centralized identity graph. By providing per-field evidence upon record ingestion, agents resolve to the same canonical identity and preserve an auditable decision history across the system.

Optimistic locking in canonical entity resolution prevents concurrent update conflicts by versioning events and validating changes before committing. This ensures that multiple agents attempting to modify the same identity record simultaneously do not overwrite each other's data, preserving audit trail integrity.