
What Makes AI Research Trustworthy
An answer can be cited, grounded, and still be wrong. Trustworthy AI requires stronger evidence, better verification, and analysts who remain in control.
Showing 1-12 of 286 results

An answer can be cited, grounded, and still be wrong. Trustworthy AI requires stronger evidence, better verification, and analysts who remain in control.

Sophisticated tools surface cyber threats in open source and dark web data

Reveal hidden risk through connected intelligence, entity resolution, and global data context.

How enriched global data uncovers insights, connections, and decision advantages.

Babel Street APIs deliver global data, analytics, and identity intelligence for faster decisions

AI-powered risk intelligence solutions help FIs analyze complex AML/KYC data faster, reduce manual friction, and make more confident compliance decisions.

How Babel Street uses Agentic AI and global intelligence to help SOCs proactively detect cyber threats before they become breaches.


Enrich existing Match scoring with locally deployed small language models that resolve semantic organization name equivalences, starting with Chinese-English pairs.

Babel Street identity record resolution helps organizations create a cleaner, more trusted identity foundation by identifying likely duplicate identities and supporting the resolution of confirmed duplicates.

Improve precision and reduce unnecessary review across multilingual screening and identity risk workflows.

Configure how names, identifiers, addresses, and other identity data affect match scores — reducing false positives and aligning decisions with operational risk priorities.
Showing 277-286 of 286 results

How Hootsuite used Babel Street language capabilities to help customers monitor and direct social media posts.

How Toshiba used name matching for increased export compliance

How Red Flag Group used Babel Street Match for enhanced due diligence

How Sensika uses Babel Street for entity extraction and base linguistics for media monitoring

How Diffeo used Babel Street entity extraction to accelerate document search for researchers.

How NYU used Babel Street Match to facilitate an international campus directory

ALIAS Technology's use of Babel Street for forensic linguistics

How CareerBuilder used Babel Street to enhance job search results

How Luminoso used Babel Street for sentiment analysis

How EMBERS project used Babel Street text analytics capabilities to build a predictive model for events in Latin America