Fremner is a deep-technology security company focused on protecting financial institutions from AI-driven identity fraud.
Our platform specializes in real-time deepfake detection for VideoKYC, digital onboarding, and regulated verification workflows.
We work with banks, fintechs, and regulated enterprises to deliver compliance-ready, AI-powered identity protection.
Founded to solve the “Crisis of Truth” in the age of Generative AI, where synthetic identities and deepfakes blur the line between real and fake.
Most security tools rely on a single detection method. Fremner AI uses a Multi-Model Ensemble combining biological, forensic, temporal, and structural signals to detect what other systems miss.
Currently in Private Preview, working closely with select design partners to redefine the future of financial identity security.
A deep technical overview of Fremner deepfake detection system, designed for CTOs, CISOs, and compliance teams evaluating production deployment.
Beyond Surface Motion: While legacy providers rely on basic movement checks (92–95% accuracy), Fremner AI utilizes deep biological signal analysis to detect authentic life.
Dataset Benchmarking: Our engine is benchmarked against industry-standard spoof datasets, maintaining high-fidelity performance across diverse demographic and lighting variables.
Audit-Ready Evidence: Every decision provides a weighted confidence score, allowing security teams to verify the forensic reasoning behind every 'Pass' or 'Fail'.
Anti-Injection Protection: Specialized defense layers designed to identify and block Man-in-the-Middle (MITM) video injection attacks.
Synthetic Identity Shield: Advanced temporal analysis to expose GAN-generated face reenactment, face-swapping, and hyper-realistic synthetic personas.
Continuous Evolution: Our ensemble architecture is updated weekly to recognize emerging adversarial techniques that bypass traditional liveness systems.
Fremner runs on secure, Azure-backed GPU infrastructure, ensuring high throughput and scalable inference for enterprise workloads.
End-to-end deepfake analysis completes in under 5 seconds, preserving user experience during live Video KYC sessions.
Designed for seamless integration with existing Video KYC, onboarding, and identity verification workflows.
Fremner is architected with privacy as a core design principle.
Fremner is designed to support evolving RBI V-CIP requirements, including enhanced forensic liveness detection and audit readiness.
Our biological rPPG-based detection satisfies the RBI’s emphasis on advanced liveness mechanisms that go beyond basic motion detection, helping institutions stay compliant as regulations evolve.