MouseCat @getmousecat
AI agents that investigate every fraud case — not just a sample. Investigate → learn → prevent. mousecat.ai Joined October 2026-
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Who's behind MouseCat? Nick — one of the core maintainers of MCP, the protocol AI agents use to talk to tools. Joe — built risk infrastructure at Coinbase. Agents + fraud plumbing, from the people who built both. If your team is drowning in flagged cases, let's talk
Writing fraud rules usually looks like: notice a pattern, write a rule, ship it, hope it doesn't block good customers. MouseCat flips it: → agents spot the pattern across investigated cases → build features from your warehouse, point-in-time.
The slowest part of fighting fraud: you often don't know it was fraud until the chargeback shows up weeks later. By then, the same pattern has hit you 200 more times. MouseCat generates labels for account takeovers and chargebacks right after investigation .
Supply has burned. robinhoodchain.blockscout.com/tx/0xb59ad0330…
Most fraud tools do one thing: score in real time, or help humans work cases. MouseCat connects both: Investigate → every flagged case, fully Learn → patterns across what agents found Prevent → new rules, backtested before they go live
What does it actually look like when an AI agent investigates a fraud case? Here's one case, start to finish
The math of a fraud queue: 100 cases flagged. 5 get a real investigation. 95 get decided by a score nobody can explain. That's where losses — and angry legit customers — come from. MouseCat's agents work all 100.
Most fraud teams review ~5% of flagged cases. The other 95% get a guess. Meet MouseCat — AI agents that investigate every single case like a senior analyst would: pulling history, checking the merchant, tracing linked accounts, even calling the phone number.
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