What does Tofu actually do?

Tofu connects to your ATS and screens applications for fraud risk, including identity theft and synthetic identities. It also analyzes interviews in real time to detect deepfakes and proxy candidates. A third feature, the AI applicant reviewer, ranks candidates against your job criteria.

How does Tofu detect fraud?

Tofu validates applicants across 4+ billion data points and its proprietary Fraudbase built from 5M+ analyzed profiles. It flags identity theft, impersonation, synthetic identities, state-sponsored actors, and location spoofing by detecting hidden patterns that reveal fake applications.

What interview platforms does Tofu support?

Tofu integrates with Zoom, Google Meet, Teams, and AI note-takers to analyze interviews in real time for synthetic audio, video, deepfakes, and candidates swapping places.

How does Tofu integrate with my ATS?

Tofu sits on top of your ATS and sees every application entering your hiring funnel. It has documented integrations with platforms like Greenhouse Recruiting, and likely supports others. Contact Tofu for a full list of compatible systems.

Can I customize Tofu's screening criteria?

Yes. You can build custom AI Screening Agents for each job and train them using profiles of your previous hires or sourced leads. Tofu's AI learns the traits that matter to your hiring and ranks applicants based on real experience and skills.

Is Tofu compliant with privacy regulations?

Tofu is SOC 2 and GDPR compliant, meaning it meets security and data protection standards. It also carries Warden AI Assurance certification.

Verification

Tofu

Candidate fraud detection for hiring and security teams.

What is Tofu?

Tofu is an AI hiring fraud detection platform that screens applicants for synthetic identities, impersonation, location spoofing, and deepfake usage, both at the application stage and in real time during interviews on Zoom, Google Meet, or Teams. It also runs AI resume review against role criteria, but its differentiating function in a hiring stack is the fraud layer, flagging proxy candidates and AI-generated overlays before a hiring manager wastes time on an interview with someone who isn't who they claim to be. Your team reviews flagged applicants directly inside your ATS; Effi Flo's role is the integration work that gets Tofu watching your full hiring funnel.

Features

What are Tofu's key features?

Catches the fraud a traditional background check misses: Real-time analysis during video interviews flags synthetic audio, face-swaps, and AI-generated overlays - addressing a newer category of fraud the deepfake interview impersonator represents, that standard background checks were never built to detect.

Validates identity before a recruiter wastes time on a fake: Cross-referencing 4+ billion data points against a proprietary fraud database flags fake applicant profiles early - so your team isn't running a full screening process on a candidate who was never real.

Built specifically for the AI-fraud era of hiring: where traditional verification checks criminal records and employment history, Tofu addresses a different risk, candidates using AI to fabricate an interview identity, a problem Gartner projects will make 1 in 4 candidate profiles fake by 2028.

Plugs into the meeting tools your team already runs: Native integration with Zoom, Google Meet, Teams, and common AI notetakers means fraud detection runs in the background of interviews your team would be conducting anyway, not as an extra step.

Network effect across every platform it protects: When a bad actor is flagged by one customer, the same identity is recognized across Tofu's entire network - protecting your agency from a fraudster who's already been caught targeting someone else.

Use Cases

How do recruiting teams use Tofu?

An in-house TA team in tech or fintech uses Tofu's fraud detection layer to flag synthetic identities and AI-generated applications the moment they hit the ATS, before a recruiter invests time reviewing a fabricated profile.
A multi-desk agency placing candidates in remote technical roles uses Tofu's deepfake and proxy-interviewer detection to catch seat-swapping and impersonation during live video interviews, a risk that has grown significantly as distributed hiring has scaled.
Teams evaluating Tofu should note it's distinct from compliance-focused background check tools like Checkr or Certn - Tofu specifically targets application fraud (synthetic profiles, deepfakes, location spoofing) rather than criminal records or employment history, and the two categories are often used together rather than as substitutes.

Fit

Who is Tofu best for?

In-house teams hiring remotely where fake applications - deepfakes, proxy interviewers, synthetic identities - have become a real and rising operational problem
Organizations needing to screen for sanctions risk, including unknowingly hiring from restricted jurisdictions, which carries real legal and compliance liability
A fit when the problem isn't verifying what's true about a real candidate but confirming the candidate is who they claim to be before any interview takes place

Pros & Cons

What are Tofu's pros and cons?

Pros

Detects multiple fraud types simultaneously across the entire hiring funnel, from application to interview
Real-time deepfake and proxy detection during live interviews without slowing down hiring process
Integrates with major ATS platforms and common interview tools, reducing implementation friction
Allows custom training on your own hire profiles, tailoring screening to your actual hiring criteria
Validates candidates against proprietary database of 5M+ analyzed profiles plus 4+ billion data points

Cons

Fraud detection relies on proprietary Fraudbase, so effectiveness depends on database completeness and updates
Deepfake detection limited to supported platforms (Zoom, Google Meet, Teams) and AI note-takers
Pricing and detailed feature tiers not disclosed in sources, requiring demo or contact for cost clarity
Requires ATS integration setup, which may need technical support depending on your system

FAQ

Frequently asked questions about Tofu

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