Pericls is a regulatory-intelligence system for fintech. You give it your company; it works out the jurisdictions and products you operate across, maps the regulations and obligations that apply, explains why each one applies, and then supports the work that follows, gap analysis, horizon scanning, regulatory roadmaps and evidence management.
The thing that makes it work is what happens before you ever arrive. Pericls does not go and search the open web for regulations each time someone enters a URL. We ingested and analysed the global fintech regulatory corpus in advance, at the time of writing, close to 15,000 fintech obligations across more than 200 jurisdictions, including supranational ones like the EU, and both numbers keep climbing. The system compares its research about your company against that established body of law rather than improvising, and that grounding is the entire accuracy story.
The value is coverage and speed rather than a single clever catch. A compliance team might take weeks or months to produce a full regulatory outlook; Pericls produces one in minutes from your jurisdictions and products. We are heading toward something closer to a full AI compliance agency, I would put the product at roughly 70% of the way there.
Val had commissioned regulatory roadmaps, horizon scans and gap analyses as a fintech CPO. He knew exactly what they cost. I had seen the same problem from the other side at Google, running payments privacy through the GDPR response. So we kept circling one question. What would an AI-native compliance team actually look like?
A compliance tool that confidently invents an obligation is worse than no tool at all. We have not seen an incorrect mapping to date, and I am not going to claim it is impossible, but the discipline is that AI proposes and never silently decides. Every mapping carries its cited reasoning and goes through human confirmation, and a reviewed map is worth more than an impressive opaque one.
Recently launched and best described as a stealth beta rather than fully public, deliberately, while we pressure-test it with real companies.