Nesil Deepfake Detector — an on-premise analysis platform that detects AI-generated manipulation in video, audio, and images within milliseconds. Your data never leaves your organization.
Product Features
AI-generated manipulation in video, audio, and images — face swaps, voice cloning, GAN-generated content — is detected, reported, and blocked within milliseconds.
Analyzes face manipulation produced by GANs, diffusion models, and classic FaceSwap algorithms at the pixel level. Detects eye asymmetry, skin texture inconsistency, blurred edge artifacts, and lighting direction mismatches.
R&D is underway for detecting AI-cloned voice recordings. A module targeting TTS, voice conversion, and GAN-based speech synthesis attacks is coming soon.
Detects inpainting, outpainting, and generative fill traces in photos. EXIF metadata integrity, compression artifacts, and frequency anomalies are examined in multiple layers.
Analyzes live video streams (RTSP, HLS, WebRTC) with millisecond latency. Integrates with video conferencing and broadcast infrastructure to prevent deepfake-based identity fraud.
Every detected anomaly gets a report with a visual evidence map, confidence score, and technical rationale — in formats suitable for court and internal investigations.
All AI processing runs on your own infrastructure; no media file is ever sent out. Works on air-gapped networks. GPU and CPU deployment options.
Mimari
Cloud-based deepfake services require sending the media out for analysis — an unacceptable risk for confidentiality and KVKK.
Nesil Deepfake Detector installs all AI models and the analysis engine on your own servers. Media under analysis never leaves the internal network. Runs in air-gapped environments, data centers, and private clouds.
Court records, CCTV footage, confidential meeting recordings — no sensitive media ever leaves.
Media containing personal data is processed entirely on local infrastructure, with processing records kept automatically.
Real-time stream analysis on local GPUs with zero network latency. High-volume batch processing supported.
Platform Modules
From video, audio, and images to live streams — analyze every dimension of AI media manipulation on one platform.
FaceSwap, FaceEnactment, and full-body manipulation detection. Frame-level and temporal inconsistency analysis.
Identify AI-generated and cloned voice recordings through spectral and prosodic analysis.
Detect AI-generated regions, inpainting, and generative manipulation in photos.
Prevent real-time deepfake identity fraud by integrating with video conferencing and broadcast infrastructure.
Evidence-grade reports suitable for court and investigations are generated automatically for every detection.
Integrate easily with existing security, content management, and workflow systems.
The Analysis Pipeline
A fully automated flow from media intake to forensic-grade reporting.
Video, audio, or images arrive via REST API, SDK, or the UI
Frame extraction, audio separation, and metadata integrity checks run
Multi-layer neural network analysis runs against 15+ deepfake model families
Detected regions are marked with heat maps and coordinates
A confidence score and classification label are produced; alarms fire past the threshold
A forensic-grade report is generated and archived with a hash
Why the Urgency?
AI-generated fake media has become the new vehicle for corporate fraud, disinformation, and identity forgery.
From CEO fraud to fabricated evidence, identity theft to misinformation — deepfakes put every industry at risk.
growth in deepfake content
in the last 3 years
in a single corporate fraud
via deepfake audio
Nesil DD tespit
accuracy rate
per-frame
analysis time
Why Nesil Deepfake Detector?
We solve the privacy, latency, and compliance problems cloud-based foreign alternatives can't — with on-premise, homegrown AI.
No media is sent to a cloud API. Sensitive recordings, facial imagery, and voice samples are processed entirely locally.
Accuracy measured on an independent test set. Recognizes 15+ model families including GAN, Diffusion, VAE, and FaceSwap.
Works on live video streams at 340ms per frame — without degrading the user experience.
Every detection is reported hash-protected, timestamped, and in court-ready format.
Local processing of media containing biometric personal data delivers KVKK compliance by design.
SLA-backed local expert support across installation, integration, and operations.
Frequently Asked Questions
See how the platform runs on your own infrastructure with a free technical demo. Proof-of-concept support included.