FaceOff unveils Behavioral AI for Service Authentication

FaceOff is a next-gen AI platform designed for high-assurance environments and is designed to combat the growing threats of synthetic fraud, deepfakes, and identity manipulation. FaceOff AI positions your organization as a first-mover by deploying compliant, edge-ready behavioral AI tailored for governments, enterprises, and OEMs. The platform's core architecture is its two deployment versions—FaceOff Full and FaceOff Lite that boasts of unwavering focus on privacy, security, and operational excellence.

Engineered to meet the critical trust requirements of government, BFSI, Payment companies, mobile phone companies and other security-sensitive sectors, FaceOff delivers robust, real-time detection and authentication capabilities where digital trust is paramount.

FaceOff AI – World’s first patented Multimodal Trust Engine

FaceOff AI is the world’s first patented multimodal trust engine, engineered to deliver real-time identity verification and behavioral analysis with the highest levels of accuracy and privacy -

● 8 Parallel AI Models: Runs simultaneous analysis for deepfake detection, emotion recognition, heart rate, oxygen saturation (SpO2), eye tracking, speech sentiment, posture analysis, and audio tone—offering a holistic understanding of user behavior and authenticity.

● Zero Cloud Dependency: Designed for secure, offline environments with on-premise API or FOAI Edge Box integration.

● Trust Factor Score (1–10): A transparent, quantifiable score that reflects user credibility and behavioral integrity in real-time.

● Privacy-First Compliance: Fully compliant with GDPR, HIPAA, and India’s DPDP Act, with audit-ready logs and architecture built for data security.

● FOAI in a Box (Edge Device): A plug-and-play solution tailored for high-security, air-gapped environments requiring zero internet access.

Shaping a New Era of Digital Trust across Sectors

FaceOff AI is redefining digital trust across industries by empowering governments, enterprises, and critical infrastructure sectors to counter synthetic fraud and identity manipulation with confidence.

FaceOff addresses these challenges through its core AI engine ACE (Adaptive Cognito Engine). ACE is a multimodal deep learning framework that analyzes eight distinct behavioral and biometric cues from short video and audio inputs. FaceOff is offered in two distinct architectural variants to cater to different deployment needs, both built on the principles of security and privacy.

FaceOff AI is also leveraging Secure Multiparty Computation (SMPC) by delivering powerful behavioral and deepfake detection capabilities without compromising user data. This makes it ideal for sensitive sectors such as government, BFSI, and critical infrastructure, where safeguarding Personally Identifiable Information (PII) and Sensitive Personal Identifiable Information (SPII) is non-negotiable.

The system operates on a Zero Data Exposure principle. The FaceOff app or SDK extracts anonymized feature vectors from raw video content locally—ensuring no video footage or sensitive data leaves the client’s premises. These vectors are encrypted using strong cryptographic protocols and sent to the FaceOff server. 

Besides, FaceOff Full offers several critical benefits - compliance with global data privacy regulations (GDPR, DPDP Act, CCPA), resilience against Advanced Persistent Threats (APT) due to decentralization, and verifiable privacy guarantees through cryptographic audits—ensuring a secure and trustworthy solution for enterprise-grade deployments.