The End of
Remote Fraud.Continuous identity verification that runs entirely in your browser.
A remote senior dev costs $30,000 in risk if they fake the interview with AI. Deep-Check validates identity continuously -- not just at login. Six independent detection layers. Zero biometric data leaves the device.
No credit card. No signup. Runs in your browser.
Four layers between your
organization and fraud
Deep-Check does not verify once and forget. It watches the entire session, fusing six independent signals in real-time.
Face Enrollment
The candidate shows their face. MediaPipe extracts 478 landmarks. No image is stored -- only a local embedding used for session matching.
Liveness Verification
Six layers run simultaneously: rPPG heartbeat, FACS micro-expressions, EfficientNet-B4 pixel analysis, CNN blendshape classifier, blink physics, and lighting reflex detection.
Behavioral Biometrics
Keystroke dynamics capture flight time, hold time, and typing rhythm. Code velocity analysis flags AI-generated copy-paste patterns in real-time.
Continuous Session Score
All signals fuse through a Bayesian ensemble in logit-space. The trust score updates every second. Anomalies trigger instant alerts to the hiring manager.
Built to be unfakeable
Not one model. Not one check. Six independent layers that would each need to be defeated simultaneously.
rPPG Heartbeat Coupling
Extracts blood volume pulse from facial video. Real skin shows cardiac rhythm; deepfakes and static images produce flat or synthetic signals. Weighted at 0.30 in the Veritas ensemble.
Keystroke DNA
Flight time, hold time, and rhythm patterns are as unique as a fingerprint. Impossible to replicate in real-time.
FACS Micro-Expressions
Action Unit analysis detects involuntary facial movements that deepfake renderers cannot reproduce at the correct temporal frequency.
EfficientNet-B4 Pixel Forensics
18.6M parameter model with multi-scale Laplacian frequency branch. Trained on 155K images across 7 datasets. AUC 0.9999, EER 0.31%. Anti-leak verified with hash deduplication and zero train/test overlap.
CNN v2 Blendshape
Separate classifier operating on blendshape coefficients extracted from the face mesh. Catches swap artifacts invisible to pixel-level analysis.
Code Forensics
Detects LLM-generated code by measuring perplexity scores, typing cadence, and paste-vs-compose velocity anomalies during live coding interviews.
Session Continuity
Continuous re-verification ensures the person who started the session is the same person throughout. Face-swap mid-session triggers instant alerts.
Deep-Check vs Onfido
Onfido verifies who someone is once, at login. Deep-Check verifies who someone is continuously, during the entire session.
| Capability | Deep-Check | Onfido |
|---|---|---|
| Identity Check at Login | Yes | Yes |
| Continuous Session Monitoring | Real-time | One-time only |
| Deepfake Detection | 6-layer stack | Basic liveness |
| Heartbeat Signal Analysis | rPPG coupling | Not available |
| Behavioral Biometrics | Keystroke DNA | Not available |
| AI-Generated Code Detection | For interviews | N/A |
| Document Forensics (ELA/EXIF) | Built-in | Add-on |
| On-Premise Deployment | Enterprise → | Cloud only |
| No Biometric Storage | Client-side | Sends to servers |
| Starting Price | Free tier | 1,500+/month |
| GDPR + EU AI Act | Full | Partial |
Document Forensics
Detect manipulated images, deepfakes in documents, and falsified metadata in grant applications, dossiers, and document verification workflows.
Error Level Analysis
Detects edited regions by comparing JPEG compression artifact levels across the image
EXIF Metadata
Identifies editing software signatures (Photoshop, GIMP, Canva) embedded in file metadata
AI Image Detection
Distinguishes real photographs from AI-generated images across Midjourney, DALL-E, and Stable Diffusion
Join the Waitlist
Get early access to Deep-Check for your organization. Continuous identity verification, on-premise deployment, and dedicated support.
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