General Questions
AI video detection is the process of identifying synthetic or AI-generated video content created using artificial intelligence and machine learning techniques. This includes detecting videos generated by tools like OpenAI Sora 2, Google Veo 3, Kling AI, Runway Gen-4, Grok Imagine, deepfakes, face-swapped content, and other forms of synthetic media.
AI-generated videos we can detect include:
- Sora 2-generated videos - OpenAI's text-to-video AI model that creates realistic videos from text prompts
- Veo 3-generated videos - Google DeepMind's text-to-video AI model with synchronized audio
- Kling AI videos - Kuaishou's AI video generator known for photorealistic human characters
- Runway Gen-4 videos - Professional-grade AI video generation with fine creative control
- Grok Imagine videos - xAI's fast AI video generator for creative content
- Pika, Luma, HeyGen, Minimax - Other popular AI video generators
- Deepfakes - Face-swapped videos and manipulated content using deep learning
- Synthetic media - Entirely AI-generated scenes, people, and environments
- Face reenactment - Videos where facial expressions and movements are manipulated
As AI video generation tools like Sora 2, Veo 3, Kling, and Grok Imagine become more accessible, detecting AI-generated content has become crucial for verifying video authenticity.
Our AI video detection system uses advanced machine learning to analyze videos for signs of AI generation, including content from Sora 2, Veo 3, Kling, Runway, Grok Imagine, deepfakes, and other synthetic media:
- Frame Analysis: We extract 16 frames from your video and analyze each one for AI-generated artifacts
- Deep Learning: An EfficientNet neural network trained on Sora 2, Veo 3, Kling, Runway, Grok, deepfake, and synthetic video datasets examines visual features
- Temporal Attention: We check for temporal inconsistencies typical of AI-generated videos from all major generators
- Pattern Recognition: The AI looks for generation artifacts from Sora, Veo, Kling, Runway, GANs, diffusion models, and deepfake techniques
- Confidence Scoring: You receive a probability score (0-100%) indicating likelihood of AI generation or manipulation
Our system is specifically trained to detect modern AI video generators like Sora 2, Veo 3, Kling AI, Runway Gen-4, and Grok Imagine, while also maintaining high accuracy on traditional deepfake detection.
Yes! Our AI video detection service is completely free to use for individual users. You can analyze videos for Sora 2, Veo 3, Kling, Runway, Grok Imagine, deepfakes, and synthetic media without any cost, subscription, or registration required.
For enterprise users with high-volume needs or API access requirements, please contact us for pricing information.
We support all common video formats including:
- .mp4 (recommended)
- .mov
- .mkv
- .webm
- .avi
For best results, we recommend uploading videos in MP4 format with H.264 encoding.
Currently, you can upload videos up to 500 MB in size. For most cases, this allows for:
- Up to 5-10 minutes of HD video
- Up to 20-30 minutes of standard definition video
If you need to analyze larger files, consider compressing them first or contact us for enterprise solutions.
Accuracy & Reliability
Our AI video detection model achieves 94%+ accuracy on benchmark datasets including FaceForensics++, Celeb-DF, DFDC, and synthetic video datasets containing Sora 2, Veo 3, Kling, Runway, and Grok Imagine style AI-generated content.
Accuracy varies by AI generation and manipulation type:
- Sora 2, Veo 3, Kling, Runway, Grok Videos: 95% accuracy on text-to-video AI content
- GAN-Generated Content: 97% accuracy on synthetic media
- Face Swap Deepfakes: 96% accuracy
- Face Reenactment: 93% accuracy
- Pika, Luma, HeyGen, Minimax: 94% accuracy
- Diffusion Model Videos: 94% accuracy
Important: No AI video detection system is 100% accurate. Results should be interpreted as probability scores, not absolute truth. As AI video generation technology like Sora 2, Veo 3, Kling, and Grok continues to evolve, we continuously update our models.
Yes, AI video detection systems can be challenged by:
- Very high-quality AI-generated videos from advanced models like Sora 2, Veo 3, and Kling AI
- Novel AI video generation techniques not seen in training data
- Hybrid content mixing real footage with AI-generated elements
- Videos intentionally crafted to evade detection
- Post-processing that removes or hides AI generation artifacts
- Emerging AI video generators using new architectures
This is why we provide probability scores rather than binary "AI-generated/real" labels. We continuously update our models to stay ahead of new AI video generation techniques, including the latest versions of Sora, Veo, Kling, Runway, Grok, and other synthetic media tools.
An "Uncertain" result (typically 40-60% confidence) means our AI cannot confidently classify the video as AI-generated or authentic. This can happen when:
- The video quality is very poor or heavily compressed
- The AI-generated content (Sora 2, Veo 3, Kling, deepfake, etc.) is highly sophisticated
- The video contains a mix of real and AI-generated elements
- The content uses cutting-edge generation techniques we haven't fully trained on
- The video is ambiguous or borderline between real and synthetic
Recommendation: For uncertain results when detecting Sora 2, Veo 3, Kling, or other AI-generated videos, we suggest:
- Manually reviewing the video for telltale signs of AI generation
- Checking the source, metadata, and context of the video
- Looking for telltale signs of AI generation (unnatural motion, temporal inconsistencies, artifacts)
- Consulting forensic experts for critical decisions
No. Our service is provided for informational purposes only and should not be used as sole evidence in legal proceedings.
For legal matters, you should:
- Consult with certified forensic experts
- Use multiple independent verification methods
- Obtain court-admissible digital forensic analysis
- Follow proper chain-of-custody procedures
Our results can serve as an initial screening tool but require professional verification for legal use.
Privacy & Security
No, we do not store your videos. We take your privacy seriously:
- ✅ Videos are deleted immediately after analysis
- ✅ We do NOT collect, store, or retain any video content
- ✅ Video URLs are used only to download and analyze, then discarded
- ✅ Only anonymous analysis results are cached (no video content)
Your video content remains completely private and is never stored on our servers. Learn more
Yes. We use industry-standard encryption:
- HTTPS/TLS encryption for all data transmission
- Encrypted uploads to our cloud storage (Wasabi)
- Secure processing in isolated environments
Your videos are protected during upload, processing, and deletion.
Analysis results are cached anonymously (identified only by video hash, not personal information) and expire automatically after a period of time.
If you opted-in to help improve our AI, you can request deletion of your contributed videos at any time by contacting us.
No. We do not sell, share, or provide your videos or analysis results to any third parties. Period.
The only exception would be if required by law enforcement with proper legal authority.
Technical Questions
We use a custom-trained EfficientNet-B0 architecture enhanced with temporal attention mechanisms.
Key features:
- Trained on 500,000+ videos from diverse datasets
- Analyzes 16 uniformly sampled frames per video
- Examines facial regions, edges, compression artifacts, and temporal consistency
- Optimized for both accuracy and speed
Learn more on our About Technology page.
Analysis typically takes about 5 seconds for most videos with our GPU-accelerated processing:
- GPU inference: ~3-5 seconds
- Video length and resolution may add time
- Your internet connection speed (for uploads)
Most videos complete in under 10 seconds.
We're currently developing an API for enterprise customers with high-volume needs.
If you're interested in API access for your business, please contact us with your use case and volume requirements.
Our current model is optimized for video analysis because it uses temporal consistency across frames as a key detection signal.
For static images, the analysis would be less accurate. We recommend using specialized image deepfake detectors for still photos.
Image detection is on our roadmap for future development.
We continuously monitor deepfake technology developments and update our model regularly to maintain effectiveness against new techniques.
Major updates typically occur:
- When new deepfake generation methods emerge
- When we acquire significant new training data
- Based on user feedback and failure cases
Our commitment is to stay ahead of the evolving deepfake landscape.