NIST-evaluated accuracy, comprehensive anti-spoofing protection, and flexible on-premises or private cloud deployment give you greater control over your biometric data.
NIST FRTE 1:1
99.83%
TAR @ 1E-6 FMR
Visa Category｜Mar. 2023
NIST FRTE 1:N
99.61%
Identification Accuracy in a 12M Face Database Search
Mugshot Category｜Jul. 2024
NIST FATE PAD
100%
TRR, No. 1 Among 82 Vendors
Passive 2D PAD｜Sep. 2023
iBeta PAD
100%
TRR, Fully On-Device
Level 2｜Mar. 2022
ISO Certifications
ISO 27001 & 27701
Information Security & Privacy Management
Core Facial Recognition
FaceMe Platform provides high-accuracy face detection, 1:1 face verification, 1:N face identification, and face search, backed by industry-leading NIST evaluation results for secure, scalable identity recognition across enterprise applications and services.
1:1 Face Verification
Compare two faces to verify a claimed identity for authentication and two-factor access control. Achieved a 99.83% true acceptance rate at a false match rate of 1 in 1 million in NIST FRTE testing (Mar. 2023).
1:N Face Search
Top-N search of a face database. Achieved 99.61% identification accuracy in a 12-million-face search evaluated by NIST FRTE (Jul. 2024).
High-Performance Face Search
Delivers fast response times at scale: 551 ms for 1 million faces, 604 ms for 10 million, and 648 ms for 60 million..
Secure Face Templates
Converts facial images into irreversible templates protected by AES-256 encryption, preventing reconstruction of the original images.
Face Image Quality Check
Checks for occlusion, blur, lighting, face angle, face size, and grayscale images before enrollment or matching.
Portrait Image Processing
Detects, rotates, aligns, and crops face images to the required dimensions for profile photos, identity records, and ID photo applications.
Liveness Detection & Anti-Spoofing
FaceMe Platform analyzes face images through server-based APIs to detect diverse spoofing attacks, including printed photos, screen replays, masks, and AI-generated deepfakes, without requiring additional user actions.
NIST FATE PAD
Ranked #1 among 82 vendors in NIST passive 2D anti-spoofing testing (Sep. 2023).
iBeta PAD
Independently tested by iBeta in accordance with ISO/IEC 30107-3, achieving a 100% TRR against 3D-printed, resin, and latex mask attacks.
Deepfake Detection
Detects AI-generated synthetic faces presented on screen as presentation attacks.
Passive 2D Anti-Spoofing
Blocks spoofing attempts without requiring user interaction or specialized cameras.
Masked-Face Support
Detects mask-wearing status (no mask, improperly worn, or properly worn) and performs anti-spoofing and liveness detection even when users are wearing masks.
Explore FaceMe SDK for on-device active and passive liveness detection and anti-spoofing across 2D RGB, RGB+IR, and 3D camera configurations.
Explore FaceMe SDK →Face & Person Attribute
FaceMe Platform combines NIST-ranked age estimation, face and person attribute analysis, and appearance-based search to deliver accurate people insights and search results, even when a face is not visible.
Age Estimation
Tested on 1M facial images from 34 countries.
Adult Verification
Determines whether a person is aged 25 or older, based on the NIST FATE benchmark (Sep 2025).
Gender & Emotion Analysis
Classifies gender and detects five emotions: neutral, happy, angry, sad, and surprised.
Person Attributes
Detects and tracks people by body shape, even without a visible face. Analyzes upper- and lower-body clothing types, more than 10 clothing colors, and accessories such as hats and bags for anonymous people counting, crowd monitoring, and appearance-based person search.
Person Re-Identification (Re-ID)
Re-identifies the same person across different cameras and time periods based on appearance features, without relying on face recognition.
People Tracker combines Re-ID, appearance search, and face recognition into a ready-to-deploy AI video analytics solution.
Explore People Tracker →Architecture, Scalability & Deployment
FaceMe Platform combines high availability, modular scalability, and zero-downtime maintenance to support reliable enterprise deployments while reducing infrastructure complexity.
High Availability
Built-in load balancing and automatic failover help maintain service availability without custom engineering.
Modular Architecture
Central, Recognizer and Matcher components can be deployed and scaled independently based on your operational requirements.
Flexible Deployment
Deploy on your own infrastructure or leading public clouds, such as AWS, Google Cloud, and Microsoft Azure, using the same architecture and API integration.
Docker Support
Container images support Red Hat and Ubuntu Linux for simplified deployment.
Horizontal Scaling
Increase processing capacity by adding additional nodes to your deployment.
Non-Disruptive Maintenance
Keep the system online during database maintenance to ensure continuous service.
Developer Integration & APIs
Choose the integration approach that best fits your application, from RESTful APIs and web-based face capture to native mobile libraries and real-time video analysis.
Integrate Your Way
Use RESTful APIs, an FAuth URL, a Web SDK, or client libraries for iOS and Android.
RESTful API
Integrate face recognition into any applications through RESTful APIs, without the complexity of a native SDK.
FAuth Web Client URL
Integrate a ready-to-use face image capture flow into existing web or mobile applications. FAuth handles camera access, face image capture, real-time quality guidance, image upload, and retry flows, eliminating the need for developers to build and maintain these functions themselves.
Live Camera Stream Analysis
Perform real-time face recognition on RTSP streams from compatible network cameras.
Recorded Video Analysis
Perform face recognition on recorded video files from external sources at up to 8× real-time speed, while live stream analysis continues.
Zero-Code Evaluation
Run a proof of concept with the console demo and test tools, then move into development with sample code.
Management, Data & Access Control
Centrally manage system operations, control administrator access, and determine where biometric data is stored.
Management Console
Monitor the real-time status of servers and cameras, configure recognition engines, and review complete API audit logs from a single console.
Secure Administrator Access
Protect console access with face and password authentication, role-based permissions, and a NIST-aligned password policy.
Face Database Management
Organize people and face images across multiple groups, and select any group as the target database for 1:N face matching.
Server & Client Compatibility
Deploy FaceMe Platform on supported servers and connect facial recognition applications across web, mobile, and edge devices.
Server Operating Systems
Deploy on supported Windows Pro, Enterprise, and Server editions, as well as Ubuntu and Red Hat Enterprise Linux.
Server Hardware
Run AI inference on supported Intel and AMD CPUs and NVIDIA GPUs.
Hybrid Edge-to-Cloud Facial Recognition
Connect FaceMe SDK-powered edge devices with FaceMe Platform for faster local facial recognition, lower bandwidth and server demands, and centralized management, on-premises or in the cloud.
Web Browser Clients
Use the FaceMe Platform Web SDK to add face recognition and identity verification to Chrome, Safari, Edge, and Firefox across supported desktop and mobile devices.
Native Mobile Clients
Use FaceMe Platform client libraries to add facial recognition and identity verification to native iOS and Android apps.
For standalone facial recognition on ARM-based edge devices, explore FaceMe SDK.
Explore FaceMe SDK →
Book a Demo
