EyesClear vs Quantexa Entity Resolution

EyesClear offers two AI-supported tools for financial-crime compliance: a Platform deployed on-premise or in a private cloud, and a separate hosted Investigations service. The Platform consolidates compliance alerts into a queue, gathers evidence, drafts case narratives and routes decisions to analysts. Cases do not close automatically; an analyst reviews, edits and signs before action. Connectors cover SWIFT, ISO 20022, MQ, Kafka, databases and files related to CRM, transactions, risk and KYC. EyesClear says Platform data and AI inference remain inside the bank’s environment rather than going to an external cloud or vendor. Investigations screens people and companies against public records and returns findings with source quotes. It can be used in a browser without integration or deployment and can pass findings to an existing case system. For a screening, it sends a subject name and derived search terms to public sources and its language models, not customer files, transactions or alerts. The service is free to financial institutions and regulators, with five credits on a new account and one credit per screening. EyesClear says it does not screen payments in real time; it addresses sanctions and name-matching alerts raised by a customer’s screening platform.

Quantexa Entity Resolution links ambiguous records across people, organizations and places to build fuller profiles. Its machine-learning models match data incrementally, using available information and, where useful, context from third-party data. Machine learning and natural-language processing prepare structured and unstructured data through cleansing, parsing, transliteration and synonym handling, with models tuned for each country. Low-code, schema-less ingestion automates data mapping and handles complex nested data. The product supports batch matching and real-time resolution at request time, including household and organization matching. Quantexa says it can scale to tens of billions of records and reports 99% matching accuracy. It can be deployed on premises or in a preferred cloud, and connects with analytics environments, data lakes and warehouses through APIs and libraries. Identified uses include financial crime, anti-money laundering, customer intelligence and fraud. Fine-grained security can tailor responses to use cases and access rights. The web, API and self-hosted product is paid, with pricing on request.