BeeSafe AI
Stopping Scams Before They Reach Your Customers
Verdict
BeeSafe AI has an exceptionally credentialed founding team — three PhDs with directly overlapping security and AI expertise, not just academic pedigree but real industry experience at Censys and Google Chrome security. The product concept is genuinely differentiated: rather than reactive fraud detection, they deploy AI agents to engage scammers and harvest mule account infrastructure data in real-time, which is a novel offensive-defensive approach. They claim financial services and government agencies are already using their intel, which if true is meaningful early traction for a 3-month-old company. Key risks: no public evidence of paying customers or revenue metrics, the 'engaging scammers directly' approach may face legal ambiguity (entrapment, jurisdiction issues), and the sales cycle for government/fintech is notoriously long. Worth watching closely — if they can show 2-3 named enterprise pilots by Demo Day, this is an S-tier team executing on a real problem.
Active Founders
Cofounder at BeeSafe AI. I have over ten years of experience as a security research and measurement scientist, using large scale data to make better security decisions. I've worked in various organizations, such as Censys, Google Chrome, and UCSD, all of which have provided unique perspectives into security at scale to protect the end user. My goal is to make the Internet a safer place for everyone, regardless of background or technical expertise.
CS PhD from UCSD and ex-CMU LTI. My objective is to reduce human-driven cyber risk after hearing so many stories from peers about how they’ve gotten scammed. I have worked in machine translation, optical character recognition, and document attribution, which was actually interrupted by a real-world ransomware attack.