Empowering Compliance teams through Unmatched Speed and Clarity
Leverage real-time client and transaction screening with ultra-low latency, full configurability and deterministic explainability
High throughput screening engine
Handles 20,000+ screening queries per second and scales horizontally – maintaining sub-5 ms latency* as you add nodes
Secure-first architecture
Engineered from the ground up in Rust to deliver memory-safe, high performance screening at enterprise scale
Fully customisable risk policies
More than 120 configurable parameters let you fine-tune the screening process to match your risk appetite
Advanced false positives reduction
Identifies and eliminates more than 20 distinct classes of false positives, saving you time and focusing your compliance review
Multi-dimensional Risk Scoring
Combines diverse data sources and algorithms into a single, explainable match score - powered by deterministic matching for audit-ready decisions
Global language coverage
Supports hundreds of languages via ultra-lightweight specialised “Nano Language Models”, to ensure accurate screening across multiple markets
Proprietary custom-built algorithms for screening
Means that we squeeze every CPU cycle to sustain more than 20,000 checks/sec* with sub-5ms latency
Secure & Resilient by design
We harden your screening stack against Common Vulnerabilities and Exposures. No unpredictable crashes during peak volumes
State of the art inverted index
We use multiple structures and algorithms to allow users to meet the most stringent SLAs on throughput and latency
Ultra-light API
Minimise latency spikes and improve consistency in API calls leveraging Axum’s type-safe middleware-friendly HTTP framework
Fearless concurrency
Our pipelines run on Tokio’s async runtime, spawning millions of lightweight tasks instead of heavyweight threads and scale linearly without context-switching overhead that drags down a lot of the traditional tech stacks
Rules and Machine Learning
We combine a deterministic rule-based approach with machine learning to improve accuracy and precision of the queries
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