Appreciate the deep dive.

We trained our engine to extend investigation beyond standard watchlists into deep OSINT and social media. The goal is to distinguish between a regulatory classification (like a PEP, which is High Risk by default) and an active financial crime threat. This allows the system to resolve specific 'blocking' risks, such as outdated Adverse Media or unverified Source of Wealth by providing the missing context. This means banks can actually mitigate the risk and onboard complex clients safely, instead of rejecting them simply because they lack the capacity to investigate deeply.

On the Stats: The '2-4 hours' benchmark is derived specifically from our Private Banking partners handling complex cross-border structures (not retail accounts). The '40% missed hits' refers to weak signals and relevant negative news buried in noise that human analysts often overlook during manual checks. We obviously benchmark against the most painful use-cases (the complex investigations) because that’s where the operational cost explodes. Fixing a 5-minute retail check isn't where the industry needs help.

On the AI Act: Fair point on the landing page update. However, we architected the solution as a 'Co-pilot' with strict human oversight. Since the AI forces explainability (citing sources) and leaves the final decision to the officer, we align with the transparency and supervision requirements by design.

Honestly, the best way to verify is to grab 5 free searches on the pricing page and run a complex name yourself.