Not everything you see is real
Explainable deepfake detection for image and video.
As infrastructure, not an afterthought.
Detection infrastructure for the AI era
Deepfake Detection
Detect face swaps, reenactments, and lip-sync manipulations across images and video with specialized neural networks.
Synthetic Media Detection
Identify fully AI-generated content from diffusion models, GANs, and other generative frameworks.
Forensic Analysis
Uncover inpainting, splicing, and post-processing manipulations through multi-layered forensic techniques.
Detesia's AI models found substantial evidence that the viral image was AI-generated.
Euronews, on the viral Maduro deepfakes, Jan 2026
Three steps to clarity
Upload or call the API
Submit media through our dashboard or integrate via REST API.
Multi-model analysis
Multiple specialized detectors analyze your media in parallel.
Explainable results
Get detailed verdicts with explanations and confidence scores.
curl -X POST https://api.detesia.com/v1/analyze \
-H "Authorization: Bearer $API_KEY" \
-F "file=@image.jpg"{
"verdict": "Substantial Evidence",
"ai_detectors": {
"match": "face_swap",
"score": 0.95
},
"forensics": {
"match": "ela_anomaly",
"score": 0.82
},
"metadata": { "software": "Photoshop" },
"watermark": { "detected": false }
}Proven on the benchmarks that matter
Our multi-detector framework is continuously evaluated against industry-standard deepfake benchmarks. We report balanced accuracy.
Deepfake Detection Challenge 2026
UK Home Office
Commended for Excellence Across All Scenarios
98.6%
DFBench
92%
Deepfake Eval 2024 Images
97.9%
MNW Benchmark Dataset
99.9%
Community Forensics
Built for teams that can't afford to guess
Law Enforcement & Defense
Verify evidence integrity and detect manipulated media in investigations and intelligence.
Insurance Fraud
Identify malicious damage claims to prevent fraudulent payouts.
Journalism & Fact-Checking
Authenticate source material before publication to maintain editorial integrity.
Platform Trust & Safety
Automatically flag synthetic and manipulated content at scale.
From the lab to production
Detesia was founded at the CISPA Helmholtz Center for Information Security, one of the world's leading cybersecurity research institutions. Funded by the German Federal Ministry of Research, Technology and Space, we bring detection methods from the lab to production, with the rigor of academic research and the speed of a startup.
Frequently Asked Questions
A deepfake is an AI-generated image, video or audio. It can depict people, objects, or events in ways that did not actually occur but appear to be real.
Our Deepfake Detection uses multiple AI models to analyze subtle patterns in media such as inconsistencies in lighting, facial movements, or compression artifacts that reveal signs of manipulation. Additionally, physical properties, metadata and watermarks can be checked, and a reverse image search can provide insights into the image's origin.
Our multi‑detector framework achieves >98% accuracy on common benchmarking datasets, and provides visual explanations for every prediction. While real-world scenarios can be more challenging, we actively monitor weaknesses and continuously improve our system to ensure it remains robust and reliable in the wild.
We provide both options: an on-premise solution for cases where data must remain in-house, and a cloud-based API that integrates seamlessly into your existing workflows.
Yes, our soft- and hardware is optimized for high performance and can detect deepfakes in real-time or batch-process large volumes of content, depending on your needs.
Yes, we prioritize data privacy and ensure our solutions comply with GDPR and other data protection regulations.
Our solution is designed for law enforcement, media companies, content platforms, financial institutions, and anyone needing to verify the authenticity of digital media.
Ready to see what's real?
Start detecting manipulated media today. No setup required.
