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Shufti MCP
Face Verification
Face Verification Software for Secure Identity Verification
Stop sophisticated spoofing before it compromises your platform. Shufti's proprietary models, trained and maintained entirely in-house, identify deepfakes, printed masks, and injected video streams through layered liveness checks and real-time frequency-domain analysis.
Independently Validated Results
Face Verification System for Advanced Fraud Prevention
Detection That Keeps Pace With New Fraud
High-resolution photos remain the most common spoofing attack at scale. Shufti’s Face Verification Technology analyses depth cues and skin-reflection patterns to rule them out at first capture.
Silicone masks, 4K replays, and real-time injection attacks remain a persistent threat. Texture and light-absorption analysis of real human skin catches them.
Synthetic and AI-generated faces are a rapidly evolving attack vector. Dual-domain analysis combines RGB with frequency-domain signals to surface them.
One Flow, Complete Identity Assurance
No head movement, no flashing lights, no prompts. Skin micro-textures, eye reflections, and replay signals are analysed in the background.
Document, AML, address, 1:N search, and age estimation route through the same RESTful API. No third-party document scanner, no separate AML provider.
Active liveness is configurable for clients who require challenge-response flows. Same SDK, same accuracy, same audit trail.
Numbers Your Compliance Team Can Defend
0.5% false rejection means legitimate users complete onboarding instead of dropping out at verification.
Met 100% of biometric accuracy goals in the U.S. Department of Homeland Security's RIVR 2025 challenge. Tested under worst-case conditions across diverse populations.
CERTIFIED LIVENESS FOR REGULATED ONBOARDING
End-to-End Face Verification Service Built to Defeat Sophisticated Fraud
Smart Face Liveness
Passive Liveness
Confirms a real human is present using texture, reflections, and depth cues. Shufti holds iBeta PAD Level 3 passive liveness certification on both Android and iOS.
Active Liveness
Prompted actions such as head movement or gestures confirm physical presence. Shufti uses 3D depth, motion, and texture analysis through the same owned engine, audit trail, and certification coverage as passive mode.
Deepfake, Replay & Injection Defence
AI deepfakes, replays, emulators, virtual cameras, and injected streams are detected in real time with layered liveness signals. Built and maintained by Shufti’s in-house data science teams, not licensed from a third party.
Multi-Stream Detection Architecture
Parallel RGB + DCT Processing
Shufti analyses visual inputs with high-frequency DCT signals to catch generative artefacts RGB-only systems can miss. Multi-signal decisioning is built in-house through Shufti’s owned detection stack and data science teams.
Region-Based Facial Analysis
Shufti analyses eyes, nose, mouth, and skin boundaries separately to detect localised manipulation full-frame checks can miss, even on partial or cropped faces. Its owned model pipeline lets each regional model update independently without production disruption.
Resolution-Aware Models
Shufti uses separate models for low-res and high-res inputs, so compressed mobile captures get consistent detection quality with no minimum quality threshold. Built for mobile-first, low-bandwidth markets across Southeast Asia, MENA, and Latin America.
Image Forensics
Brings Hidden Tampering to the Surface
Shufti enhances areas where fraud leaves traces: edge seams, texture mismatches, and abnormal noise. Its AI detects near-invisible tampering on low-quality images, beyond surface-level checks.
Reads the Image, Not the Metadata
Shufti detects fraud from image content itself, even when metadata, camera signatures, or timestamps are removed. In-house models hold up on repackaged or re-saved files, without third-party dependency.
Attention map for every decision
Every flagged image includes a colour-coded attention map showing natural, moderate, and high-anomaly zones. Explainable AI shows fraud teams where and why risk was flagged, supporting EU AI Act readiness.
Continuous Learning Pipeline
Synthetic Training Data Generation
Shufti uses multiple deepfake frameworks to generate attack-like training data, including face swaps, compression, and replay artefacts. Its owned training pipeline absorbs new attack patterns without third-party dependency.
Retrospective Biometric Audit
Rescan past biometric records with current deepfake models to flag high-risk accounts for review, re-verification, or closure. Continuous biometric risk monitoring after onboarding, aligned with AMLD6 and equivalent frameworks.
Modular Production Updates
Update models independently without disrupting live services. Shufti monitors production shifts to catch degradation early, resolve issues faster, and reduce downtime risk.
Single API, Seamless Integration
Build fully customisable verification flows with seamless backend integration.
- Gain full control by customising verification flows end-to-end.
- Integrate seamlessly with your backend for quick implementation.
- Design flexible verification journeys tailored to your users.
Launch a native verification experience in your mobile app within minutes.
- Launch native verification within minutes on iOS or Android.
- Use ready-made UI with camera, capture, and real-time feedback.
- Customise flows to fit seamlessly into your mobile app.
With KYC Journey Builder, create personalised verification journeys without writing a single line of code.
- Customise your journey effortlessly with drag-and-drop functionality.
- Instantly see how your verification flow looks for your users.
- Easily connect with Hosted Verification for a consistent, branded experience.
Run Shufti within your own identical-capability infrastructure for maximum data control and privacy.
- Keep all sensitive information in-house to meet strict governance and data residency requirements.
- Keep sensitive information fully private and secure in-house.
- Deploy in highly regulated sectors without compromising compliance.
Where AI Face Verification Fits Best
Built For Regulated & High-Risk Businesses
Built For Regulated & High-Risk Businesses
Verify the seller is real at onboarding, then prevent re-joins with duplicate detection and optional 1:N matching across verified records.
Recognized as a G2 Leader, Summer 2026
Shufti has earned multiple G2 distinctions this season, rated by real users and trusted by enterprises worldwide.
See All Reviews
Don’t just take our word for it, hear from our customers
The Confidence Our Clients Share
The future of digital identity is defined by trust, interoperability, and regulatory alignment, so our partnership with Shufti reinforces DevCode Identity’s commitment to supporting our global customers with the most secure, best-in-class, compliant identity verification solutions available today.
Combining our Conversion Driven Compliance Orchestration Platform with Shufti’s global KYC and IDV capabilities allows our customers not only to navigate complex regulatory demands but also to maintain a seamless customer onboarding experience with the highest achievable conversion rates.
We’re proud to continue our partnership with Shufti as we expand into new jurisdictions.
Shufti’s verification technology not only strengthens our compliance framework but also ensures our players enjoy a smooth, secure onboarding experience.
We aim to offer our clients and their traders the very best tools with which to do their jobs, we’re excited to be able to work with Shufti.
They’re a leading company, and we’re looking forward to offering their solutions to our clients through our CRM.
The relationship with Shufti was born out of frustration with an existing provider, so we started our discussion with Shufti.
The response time was excellent, from the start of speaking to sales to getting up and running with the demo.
Everything you need to know in one place
Frequently Asked Questions
Is face verification only for onboarding with an ID?
No. Use it anywhere fraud shows up, login challenges, account recovery, withdrawals, payouts, and resets. It can also match to an ID photo when required.
How does face verification detect deepfakes?
Face verification systems apply multiple detection layers. Shufti uses RGB colour-space analysis combined with DCT frequency-domain decomposition to identify synthetic artefacts in the captured image. This detects AI-generated faces, digitally manipulated photos, and injected data streams that bypass the camera.
What levels of iBeta liveness certification does Shufti provide?
Shufti provides iBeta-certified liveness detection across Level 1, Level 2, and Level 3 testing. These levels assess presentation attack detection against increasingly advanced spoofing attempts, from basic printed attacks to higher-quality replays, masks, and more sophisticated presentation attacks.
Can historic KYC selfies be rescanned for deepfakes?
Yes. Shufti's retrospective deepfake audit tool, available through AWS Marketplace, rescans biometric records collected during previous onboarding against current-generation deepfake detection models. This identifies selfies that passed verification at the time but would fail under today's detection standards.
What happens when a user wears glasses, a headscarf, or has a facial difference?
The 68-landmark facial mapping and 3D depth reconstruction are designed to work across a range of facial presentations. iBeta Level 2 testing includes demographic diversity requirements.
Prove the Person Is Real Before Risk Moves Forward
Stop deepfakes, masks, and injected video streams with face verification built on Shufti’s owned stack. iBeta Level 3 certified, DHS RIVR 2025 validated, and deployable on-premise or in sovereign cloud.
Your Go-To for KYC/AML & Fraud
Resources
3 June, 2026
The Deepfake Detection Gap
How many of your verified customers never existed. Shows how synthetic and deepfake identities pass KYC, and how the Blind Spot Audit finds the ones that did pass.
Report
