Designed a deep learning system to detect deepfake videos by analyzing both visual and audio inconsistencies. Combined Vision Transformers (ViTs) for frame-level analysis with spectrogram-based audio inspection to enhance accuracy. Implemented a dual input architecture to evaluate temporal and lip-sync mismatches. Integrated the model into a user-friendly interface for real-time detection and validation.