Neural Defend is a deepfake detection platform that analyzes audio, video, images, and documents to identify AI-generated or manipulated content. The platform was developed by researchers from MIT and Intel. The system provides detection capabilities across multiple media types including synthetic video content, manipulated speech, AI-generated imagery, and tampered documents. It includes face-swap detection to prevent unauthorized identity swapping and a Unified Super Liveness feature that combines liveness detection with deepfake and face-swap detection. The platform processes files in under one second and claims detection accuracy rates. It has analyzed over 10 million files and maintains a 99.9% uptime SLA. Neural Defend holds ISO 27001 and SOC 2 Type 2 security certifications. The detection system analyzes various elements including pixel shifts and lighting patterns to identify manipulations. It operates through an API that can be integrated into existing security workflows. The platform is designed for organizations requiring protection against AI-generated fraud and synthetic media threats.