Matching Engine

Double-sided screening for messy real-world records.

Hunter screens customer records against Nominodata-powered compliance datasets using NamesPlus name expansion, address verification, Jaro-Winkler scoring, source sync controls, and usage-based costing.

Request AccessView Architecture
ScreeningExplainable screening workflow
Sync ControlsGoverned dataset synchronization
NamesPlusGiven-name stems and variants
S3 SyncIn-memory archive decompression

Architecture

Separate the watchlist source from the customer record pool.

The Hunter Matching Gateway keeps Nominodata download channels, normalized compliance data, and customer candidate pools distinct. That separation supports safer sync operations, clear lineage, and metered screening without blending customer records into provider datasets.

  1. 01
    Sync

    Download Nominodata ZIP archives from S3 channels and decompress in memory.

  2. 02
    Normalize

    Seed watchlists, NamesPlus variants, country mappings, and address rules.

  3. 03
    Expand

    Generate candidate name forms using stems, nicknames, token order, and phonetics.

  4. 04
    Score

    Combine deterministic locks with Jaro-Winkler similarity and evidence weighting.

  5. 05
    Bill

    Record checks, sync runs, estimates, invoice lines, and printable client summaries.

Matching Logic

Precision where it matters. Flexibility where names drift.

Hunter combines hard mismatch rules with fuzzy matching so the engine catches real variants without accepting impossible records.

NamesPlus Expansion

Given names are mapped to stems and known variants, so Robert can resolve to Bob and William can resolve to Bill without pretending those variants are source-backed aliases.

Bag-of-Words Alignment

Name tokens are compared even when middle names are missing, initials are used, or token order is reversed across jurisdictions and source formats.

Address Verification

Directionals, street types, units, and countries are standardized while building numbers remain locked. A house-number conflict is treated as an immediate mismatch.

Jaro-Winkler Similarity

Fuzzy name and street comparisons use Jaro-Winkler scoring, with prefix sensitivity tuned for practical compliance screening.

Evidence Trail

Every candidate match can carry evidence: exact name, variant, token overlap, DOB, country, identifier, address, PEP role, or negative evidence.

Metered Ledger

Match requests, sync operations, cost estimates, invoice line items, and printable client invoices are tracked as part of the gateway workflow.

MCP Connector

The Matching Engine can be exposed through a Hunter MCP connector, allowing approved AI agents and internal compliance assistants to run governed name matching, variant expansion, and screening-support queries without exposing credentials or raw production systems. Designed for controlled workflows where analysts need explainable matching results inside the tools they already use.

Coverage

Nominodata-powered datasets for compliance and risk workflows.

The gateway is designed to ingest principal Nominodata risk, KYC, and compliance feeds and expose them through a coherent screening surface.

  • NamePLUSGlobal given-name variants and stems for expansion matching.
  • Sanctions & WatchlistsInternational, regional, and governmental risk listings.
  • PEP / REPPolitically exposed persons, relatives, and close associates.
  • CRB, HIDTA, HIFCASpecialized business, trafficking, financial-crime, zip-code, and area-code risk datasets.
  • Adverse MediaOpen-source risk indicators and profile screening signals.
  • Human Trafficking RiskStructured risk dataset for trafficking-related screening.
  • Medical ExclusionsHealthcare exclusion lists for regulated industry screening.

API Surface

Simple endpoints for screening, syncing, and administration.

The reference gateway runs as a Python service with SQLite in local sandbox mode and can be adapted for AWS EC2 deployment.

MCP Connector

The Matching Engine can be exposed through a Hunter MCP connector, allowing approved AI agents and internal compliance assistants to run governed name matching, variant expansion, and screening-support queries. The connector is designed for controlled workflows where analysts need explainable matching results inside the tools they already use — without exposing credentials or raw production systems.

POST/api/match

Drag-and-drop CSV screening endpoint with Jaro-Winkler scoring and evidence output.

POST/api/datasets/sync

Asynchronous Nominodata dataset sync with in-memory ZIP decompression and seeding.

POST/api/forgot-password

Token-based administrative console password reset workflow.

Get started

Screen names, addresses, and entities without losing the evidence.

Hunter gives teams a practical matching layer for compliance data: explainable scores, source-aware candidate matches, sync controls, and usage reporting that can support client billing.

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