Match real-world entities, not just names
Resolve messy, multilingual, incomplete and inconsistent entity data with an API built for compliance-grade matching, with richer context, configurable logic and explainable AI.
Capabilities
Extensive configurability
- 120+ parameters tune matching sensitivity across names, identifiers, dates, locations and custom fields.
- Context filters refine matches by scenario, data source and risk logic.
API-first
- Core integration: connect directly with internal systems, workflows and data pipelines.
- Match APIs: push results, match scores and explanations into existing workflows.
Efficient & effective
- Increased detection: surface hundreds of match variations using AI and contextual signals.
- Higher accuracy: minimise false positives by suppressing 20+ classes of irrelevant matches.
Low latency, high throughput
- Process 20,000+ names per second while keeping latency under 5ms.
- Auto-tuning automatically optimises config and AI around your data.
Built to replace or enhance legacy screening
Dynamic scoring
Multi-dimensional risk scoring that combines machine learning and rules.
vs traditional fuzzy matching that floods you with false positives
Explainable
A detailed, audit-ready rationale on every match, defensible to regulators.
vs black-box scores compliance teams can't justify
Policy tuning
120+ parameters tuned per scenario, market and client type.
vs single-threshold engines blind to context
Multi-lingual
Script-aware translation and NLP analytics, bespoke per language.
vs transliteration rules that miss the latest variations
20,000+
checks per second
<5ms
decision latency
120+
tunable parameters
6m+
risk profiles · 1.1m+ PEPs
See a clearer path to compliance
We'll show you explainable screening tuned to your policies, on your data.
Follow us on LinkedIn