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Deepfaic Documentation

website·Indexed 31 days ago

https://docs.deepfaic.com

Documentation for the Deepfaic platform and Deepfaic Edge, an offline runtime for deepfake analysis. Includes API references for media upload, job management, and usage metrics, as well as details on specialized models for facial detection, temporal coherence, TTS audio, and Stable Diffusion.

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What's inside Deepfaic

  1. Overview of Deepfaic Deepfake Detection Platform

    Deepfaic is an enterprise-grade, multi-modal deepfake detection platform designed to authenticate synthetic content across video, audio, images, and text. It provides high-precision detection (95–99% accuracy) with low latency, suitable for real-time fraud prevention, KYC/e-KYC onboarding, content moderation, and regulatory compliance. The platform is available via feature-rich APIs, SDKs, and optional on-premises deployment.

  2. Overview of the Temporal Coherence Detection Model

    The Temporal Coherence Detection Model identifies video deepfakes by analyzing frame-level visual artifacts and cross-frame temporal irregularities. It is specifically designed to detect inconsistencies in geometry, texture, and blending across space and time that often evade traditional CNN-based detectors and human observers.

  3. Overview of Deepfaic Meeting Bots

    Deepfaic Meeting Bots provide near real-time deepfake detection for virtual meetings across video, audio, and text communications. The bots integrate with video conferencing platforms to detect AI-generated media and ensure authentic interactions.

  4. Overview of Deepfaic Multimodal Deepfake Detection

    Deepfaic is an API-first platform designed for real-time, multimodal deepfake detection and content integrity. It allows enterprises, platforms, and governments to verify the authenticity of digital media across multiple formats, including video, audio, images, text, and synthetic meeting scenarios, to combat fraud, impersonation, and misinformation.

  5. Overview of Deepfaic Realtime Streaming

    Deepfaic Realtime Streaming allows developers to send live video and audio streams to API endpoints for near real-time deepfake analysis. This feature is designed for building applications that detect and respond to manipulated content as it occurs, specifically for use cases in real-time content verification and security applications. Note: This feature is currently in development and will be available soon.

  6. Overview of Audio Detection Model capabilities

    The Audio Detection Model uses spectral analysis and deep neural networks to identify audio manipulations, including AI-generated voices, voice conversion, and synthetic speech attacks created by Text-to-Speech (TTS) synthesizers and neural vocoders. Key capabilities include detecting pitch and tempo modifications and supporting both mono and stereo audio streams.

  7. Overview of Deepfaic Multimodal Deepfake Detection

    Deepfaic is an API-first platform designed for real-time, multimodal deepfake detection and content integrity. It allows enterprises, platforms, and governments to verify the authenticity of digital media across multiple formats, including video, audio, images, text, and synthetic meeting scenarios, to prevent fraud, impersonation, and misinformation.

  8. Overview of Noise-Robust TTS Detection Model

    The Noise-Robust TTS Detection Model is designed to identify AI-generated speech, voice cloning, and impersonations, even in real-world conditions containing background noise, compression, or recording artifacts. It utilizes a combination of self-supervised speech representations and low-level acoustic signal analysis to detect synthetic inconsistencies.

  9. Overview of Deepfaic Edge impersonation checks

    Deepfaic Edge allows developers to run impersonation checks entirely within their own environment. A typical implementation involves a Python-based workflow that stages media files into the edge runtime uploads directory, creates an edge job, polls a partial job endpoint for progress, and retrieves the final job record containing scores and total pipeline processing time.

  10. Overview of Deepfaic Scam Bot capabilities

    Deepfaic Scam Bot is an intelligent conversational bot providing real-time protection against scams, malicious links, and fraudulent communications. It uses natural language processing to analyze conversation intent, detect suspicious patterns, and identify harmful content.

  11. Overview of Stable Diffusion Detection Model

    The Stable Diffusion Detection Model is designed to identify content generated by next-generation AI systems such as Stable Diffusion, DALL-E, and Midjourney. Unlike traditional detection methods, it focuses on low-level visual artifacts and diffusion-specific signatures that are invisible to the human eye.

  12. Facial Detection Model capabilities and features

    The Facial Detection Model identifies synthetic media manipulations (deepfakes) created via GANs, autoencoders, and diffusion models by analyzing spatial and temporal inconsistencies. Key technical capabilities include:

    • Precision Detection: Frame-level face detection supporting faces as small as 20×20 pixels.
    • Resolution Robustness: Maintains accuracy for content down to 360p resolution.
    • Frame Rate Flexibility: Seamlessly processes videos with various frame rates.
    • Smart Cropping: Intelligent isolation of faces for focused analysis.