Data
Hunter combines Nominodata-powered compliance datasets with Hunter-owned data, public records, partner feeds, and customer uploads — then normalizes everything into a single entity model for search, enrichment, matching, and relationship discovery.
Request data access →Hunter Data is a preferred Nominodata partner, giving the platform access to Nominodata-powered compliance, risk, KYC, sanctions, PEP/REP, NamesPlus, adverse media, and specialized risk datasets. Hunter expands that foundation with Hunter-owned data, public records, partner feeds, and customer uploads, then normalizes it into one coherent layer for search, enrichment, matching, and relationship discovery.
OFAC, UN, EU, HMT, DFAT, and 40+ additional sanctions lists, updated continuously.
Politically exposed persons across 200+ jurisdictions with role, tenure, and relationship data.
Relatives and close associates of PEPs, with relationship type and confidence scoring.
Proprietary name expansion covering transliterations, aliases, nicknames, and script variants.
Structured adverse media signals from global news sources, categorized by risk type.
Sector-specific risk datasets including enforcement actions, debarment lists, and fraud registries.
Law enforcement, regulatory, and industry watchlists normalized into a unified entity model.
Coverage
Every record in the Hunter data layer originates from one of five source types. Each is ingested, normalized, and enriched before being exposed through the API.
Normalization
Raw records from five source types are ingested, normalized against a unified entity model, enriched with cross-dataset signals, and served through a single API layer. Lineage is preserved at every step.
Records arrive from all five source types — Nominodata feeds, Hunter-owned data, public records, partner feeds, and customer uploads.
Hunter applies a unified entity model: names are standardized, identifiers are mapped, dates are normalized, and jurisdictions are resolved.
Each entity is enriched with signals from the full data layer — cross-referencing identifiers, resolving aliases, and attaching relationship metadata.
The normalized, enriched data layer is exposed through the Search API, Relationship Engine, and Matching Engine — all via a single REST endpoint.