AML Crypto Checks for Safer Transactions

Baltex uses a multi-layer risk engine that combines machine-learning behavioral models, graph analysis, clustering heuristics, and exposure mapping. The system evaluates transaction history, flow patterns, network connections, and links to known illicit entities to generate a transparent and evidence-based risk score.

Our intelligence layer is refreshed continuously using data from global anti-fraud agencies, sanctions authorities, cybersecurity partners, law-enforcement reports, and confirmed incident feeds. All new data passes through validation, deduplication, and attribution pipelines before being integrated into the core risk graph.

No. Baltex operates as a fully non-custodial analytics layer. The system never touches user funds or private credentials and relies exclusively on publicly available blockchain metadata, behavioral signatures, and external intelligence sources.

Baltex performs analytics across major L1 and L2 ecosystems and thousands of assets. Transaction data is normalized into a unified behavioral model, enabling consistent multi-chain risk scoring, cross-chain exposure detection, and tracking of laundering patterns involving DEXs, bridges, and mixer routes