Verify by TaiLR Made AI

Verify runs resume fraud detection entirely in the browser without sending candidate data to external servers

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Verify runs resume fraud detection entirely in the browser without sending candidate data to external servers. When you upload a resume through the Chrome or Edge extension, it performs forensic signal analysis locally on your machine. This approach means no data transmission, no scraping, and no storage on remote systems. The architecture prioritizes privacy while maintaining speed.

The detection pipeline analyzes multiple fraud vectors simultaneously. It scans for AI-generated content by examining writing patterns and linguistic markers that distinguish machine-generated text from human-authored resumes. The system flags diploma mills by cross-referencing educational institutions against known databases of unaccredited schools. Timeline manipulation detection identifies gaps, overlaps, or chronological inconsistencies in employment history. It also looks for stolen identity indicators by analyzing patterns typical of identity fraud.

Processing happens in under 20 seconds. That's fast compared to traditional methods. Manual resume audits typically take about 15 minutes per candidate. The automated approach compresses this verification work into a fraction of the time while running the same checks a human auditor would perform.

Output comes as real-time red flag alerts. When the system detects potential issues, it surfaces them immediately rather than generating a delayed report. This lets recruiters make quick decisions about whether to proceed with a candidate or conduct deeper investigation before scheduling interviews.

The API enables workflow automation for teams using applicant tracking systems. Developers can integrate Verify into existing hiring pipelines so resume verification happens automatically as applications arrive. The API provides the same detection capabilities as the browser extension without feature restrictions. Both access methods cost the same and offer identical functionality.

Integration with ATS platforms means verification can become part of the standard screening process rather than a separate manual step. Verify works alongside automation platforms too, fitting into broader recruitment technology stacks. Chrome and Edge support covers most recruiter workflows since these browsers dominate enterprise environments.

Pricing runs ten cents per check. There's no feature gating between the extension and API. You get full access to all detection capabilities regardless of how you're using Verify. No subscription tiers or usage limits beyond the per-check fee.

Technical limitations matter here. Accuracy drops with non-screen-readable resume formats or unusual layouts. The system relies on being able to parse text and structure from the document. If the resume uses an unconventional format or contains elements that don't render properly, detection quality suffers. Verify can't confirm whether a person actually exists, only whether the resume itself shows signs of fabrication. This distinction is important. A flagged resume indicates potential fraud but doesn't definitively prove the candidate is fake. Similarly, a clean scan doesn't guarantee authenticity.

Format compatibility is not universal. Some resume layouts will not work with the detection algorithms. Verify performs best with standard document structures where text extraction works cleanly. Edge cases with complex formatting or embedded graphics may produce unreliable results.

The founder brings over 25 years of recruitment operations experience to the product design. This background shaped Verify's focus on practical verification needs rather than theoretical fraud detection. The local processing architecture reflects real-world concerns about candidate data privacy in hiring contexts.