Tofu is an AI-powered candidate fraud detection company built to defend the hiring process against a fast-growing wave of AI-enabled deception. As remote hiring and generative AI have become ubiquitous, employers increasingly face fraudulent applicants who use synthetic identities, deepfaked video, location spoofing, and proxy interviewers, in some cases tied to organized or state-sponsored fraud schemes. Tofu addresses this emerging threat by detecting these signals across the full hiring funnel, from resume screening through live interviews.
The platform sits at the intersection of recruiting and security, giving both talent teams and security teams a shared trust layer over the candidate pipeline. Tofu analyzes applications and interviews for indicators of synthetic identities, manipulated media, anomalous locations, and impersonation, flagging suspicious candidates before they advance or are hired. This is particularly important as AI resume-screening tools accelerate the funnel and as deepfake technology makes it harder for human interviewers to spot impostors in real time.
By focusing specifically on fraud and deepfake detection rather than general screening or sourcing, Tofu occupies a distinct and timely niche. Its value grows as more companies adopt remote and AI-assisted hiring workflows that, without safeguards, expand the attack surface for fraud. Detecting a fraudulent hire early prevents serious downstream risks, from data theft to compliance violations.
Tofu raised a $1.2M pre-seed round from Night Capital, Garage Capital, Wayfinder Ventures, and Ritual Capital. As an early-stage company, it is building purpose-built defenses for a problem that has rapidly moved up the priority list for hiring and security leaders confronting AI-driven candidate fraud.