Facia
Deepfake-aware liveness and facial verification that confirms the face is real—in under a second.
What is Facia?
Facia is an AI-powered identity verification platform that combines liveness detection, deepfake detection, and facial recognition into a single solution. It helps businesses and government organizations confirm that a person is physically present and that the face presented is real, not a synthetic or manipulated image. The platform's headline feature is DeepLiveness, which layers deepfake detection on top of standard liveness checks to catch AI-generated faces, synthetic identities, and live facial overlays. Designed for real-time use, Facia claims sub-second response times and industry-leading accuracy rates, with its latest algorithm reducing FAR to 0.06% and FRR to 0.3%. It is iBeta Level 2 certified and protects against 56+ types of spoofing attacks while working in low-light conditions and with accessories like hats and glasses. The platform also offers 1:1 and 1:N face matching, age estimation, and deepfake detection for images and videos, making it suitable for KYC onboarding, secure access, live video calls, and other verification flows. Facia provides lightweight SDKs for iOS and Android (~5MB), robust RESTful APIs, and cross-platform support with no specific hardware requirements. This makes it easy for product and engineering teams to embed deepfake-aware verification into existing applications. Headquartered in London, Facia serves a range of industries including banking, KYC providers, iGaming, cybersecurity, and hiring platforms, positioning itself as a trust and security layer for the era of advanced deepfakes.
SpecificationsAI-estimated
Key Features of Facia
Use Cases for Facia
Liveness Detection for Customer Onboarding
Detect spoofing, replay attempts, and AI-generated faces during digital onboarding to strengthen KYC flows without adding friction.
Deepfake Detection in Identity Verification
Detect deepfake images, manipulated videos, synthetic selfies, and face swaps throughout the KYC journey in real time.
Video Call Deepfake Detection
Identify synthetic faces and real-time deepfake overlays during live video meetings, interviews, or support calls.
Step-Up Authentication for High-Risk Actions
Detect risk signals during critical account actions and trigger face-based step-up verification before sensitive operations continue.
Biometric Enrollment & Re-Verification
Prevent spoofing, mismatches, and synthetic identities during biometric enrollment, recovery, or re-verification flows.
Surveillance & Access Security Detection
Detect persons of interest across live video streams and identify spoofing attempts at secure entry points.
How to use Facia?
Request Access
Contact Facia through the website to get API credentials and evaluate integration options for your specific use case.
Integrate SDK or API
Add the lightweight iOS/Android SDK (~5MB) or use the RESTful APIs to connect Facia to your app or service.
Configure Verification Flows
Choose liveness detection, deepfake detection, and/or facial recognition modes, then customize settings for onboarding, video calls, or other flows.
Run Live Verification
Trigger verification in your application. Facia returns results in under a second, flagging synthetic faces, spoofs, or mismatches in real time.
Monitor Results
Review detection outcomes and use the real-time signals to support security decisions, compliance requirements, and ongoing optimization.
Pros & Cons of Facia
Pros
- Industry-leading accuracy with 0.06% FAR and 0.3% FRR in its latest algorithm.
- DeepLiveness adds a deepfake detection layer to standard liveness, catching synthetic identities in real time.
- Certified iBeta Level 2 and NIST standards compliant.
- Protects against 56+ types of spoofing attacks, including AI-generated faces and replay attempts.
- Lightweight SDKs with no special hardware requirements and flexible RESTful API integration.
Cons
- Pricing is not publicly disclosed; enterprises must contact sales to get a quote.
- Biometric data collection may raise privacy, consent, and regulatory concerns for some organizations and end users.
- The solution is primarily aimed at enterprise and government customers, so smaller businesses or individual users may find it excessive.
- Accuracy claims are based on vendor-controlled lab conditions and testimonials; real-world results can vary with camera quality and environmental factors.
Frequently Asked Questions
What is DeepLiveness?
DeepLiveness is Facia's multi-modal liveness and deepfake detection layer. It not only confirms presence but also verifies the face is real by using RGB texture, motion analysis, depth mapping, and neural anomaly detection.
What accuracy rates does Facia claim?
Facia's latest algorithm update reduced FAR to 0.06% and FRR to 0.3%, which the company describes as the lowest rates in the industry. Its liveness detection is also iBeta Level 2 certified with 0% FAR at <1% FRR.
What spoofing attacks does Facia protect against?
Facia protects against 56+ types of spoofing attacks, including replay attempts, AI-generated faces, synthetic identities, and face swaps.
Does Facia work with hats, glasses, or in low light?
Yes, the liveness detection solution is designed to work with hats and glasses and in low-light conditions.
What platforms are supported?
Facia offers compatible SDKs for iOS and Android (~5MB), cross-platform support, and robust RESTful APIs, with no specific hardware requirements.
What is the typical response time?
Facia claims lightning-fast liveness detection with a response time of under one second.
Which industries use Facia?
Facia is used by businesses and governments across banking, KYC providers, iGaming, cybersecurity, hiring and interviewing software, and access control, among other industries.
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