Relationship Engine
Hunter resolves entities, surfaces connections, and scores confidence across Nominodata-powered data, Hunter-owned data, public records, partner feeds, and customer uploads — all through a single API.
Capabilities
The Relationship Engine operates across all five Hunter data source types. Every capability is exposed through the REST API — no separate integration required.
Hunter resolves the same real-world entity across multiple records and datasets — matching on name variants, identifiers, addresses, and contextual signals. Duplicate records collapse into a single canonical entity with full source lineage.
Powered by NamesPlus name expansion, Jaro-Winkler distance, and bag-of-words scoring.
Entities resolved across Nominodata-powered data, Hunter-owned data, public records, partner feeds, and customer uploads are stitched into a unified graph. A person appearing in sanctions data, a corporate registry, and a customer upload becomes one node.
Identifiers, aliases, and attributes from all five source types are merged at the entity level.
Hunter surfaces connections between entities — ownership, control, family, and associate relationships — drawn from structured data across the full data layer. Relationships are typed, directional, and attributed to their source.
Supports depth-limited graph traversal via the Relationship Queries endpoint.
Every resolved entity and every relationship edge carries a confidence score derived from the strength of the matching evidence. Scores are transparent — you can inspect the signals that produced them.
Scores range 0–1. Configurable thresholds for search, matching, and monitoring.
Hunter tracks changes to entities and relationships over time. Sanctions additions and removals, PEP role changes, ownership transfers, and adverse media events are timestamped and preserved in the entity history.
Entity monitoring delivers change events via webhook or polling.
The full entity graph is queryable via the Relationship Queries endpoint. Traverse ownership chains, surface hidden connections, and identify shared identifiers across datasets — all in a single API call.
Depth up to 4 hops. Filter by relationship type and minimum confidence.
How it works
The Relationship Engine runs continuously across the full Hunter data layer. Results are available through the API as soon as records are ingested.
Records arrive from all five source types. Each record is parsed, normalized, and assigned a provisional entity identifier.
Hunter applies entity resolution across the full data layer — collapsing duplicate records into canonical entities with confidence scores.
Resolved entities are stitched across datasets. A person in sanctions data, a corporate registry, and a customer upload becomes one node.
The entity graph is queryable via the Relationship Queries endpoint. Traverse, filter, and score — all in a single API call.
API surface
The Relationship Engine is fully accessible through the Hunter REST API. No additional integration layer required.
/api/entities/:id/enrichRetrieve full enrichment data for a resolved entity — identifiers, aliases, relationships, and risk signals.
/api/relationships/queryQuery the relationship graph for connections between entities. Supports depth-limited traversal and confidence thresholds.
/api/monitorRegister entities for continuous monitoring. Receive change events via webhook when relationships or risk signals update.