ZSure is an enterprise deepfake detection platform built by Hypotenuse Analytics. It exposes synthetic video, AI voice clones, and faked identity documents before fraud scales — verifying any image, video, or audio file in seconds.
ZSure runs a three-model detection ensemble that analyzes media across multiple modalities at once — facial geometry and micro-artifacts in video, spectral signatures in audio, and generative fingerprints in images. Instead of relying on a single classifier, the models cross-validate each other to produce a verdict with a confidence score.
- Video — face-swap deepfakes, lip-sync manipulation, and fully synthetic footage
- Audio — cloned voices, synthetic speech, and AI-generated call audio
- Images — generated portraits, edited documents, and synthetic KYC selfies
You can try it yourself on the Media Verifier — upload a file or paste a URL and get a verdict in seconds.
Accuracy depends on the quality and length of the media. ZSure's ensemble is tuned for real-world attack conditions — compressed social-media re-uploads, partial faces, noisy call audio — not just clean lab samples. Every result ships with a confidence score so your team can set risk thresholds that match your fraud tolerance. For a live evaluation against your own data, book a demo.
No. Our principle is transient processing — uploaded media is analyzed in memory and deleted immediately after the result is produced. We never train models on your media, never sell data, and never retain content beyond short-lived diagnostic logs that contain only the verdict and model scores. Full details are in our Privacy Policy.
Yes. ZSure's audio models are built specifically for the three-second-clone problem — identifying synthetic speech generated by modern voice-cloning tools even in low-bitrate telephony audio. This defends against CEO-fraud calls, family emergency scams, and fake KYC voice verification bypasses.
ZSure screens onboarding media for signs of synthetic identity fraud — GAN-generated portrait artifacts, document texture inconsistencies, and replay or injection attacks during selfie-video KYC. It slots into your existing onboarding flow as a verification layer before accounts are created.
Yes. The engine is built for “real-world speed” — most scans return a verdict in seconds, fast enough for call-center screening, onboarding flows, and newsroom verification workflows. Enterprise deployments support streaming and API-based integration for inline checks.
Yes. ZSure exposes REST APIs and SDK integration options so detection can be embedded directly into your onboarding, transaction-monitoring, or content-moderation pipelines. Volume pricing, SLAs, and private deployment options are covered during an enterprise briefing — contact us to scope your integration.
ZSure is operated from Noida, India, and designed around India's evolving synthetic-media framework — including the DPDP Act 2023 for data protection and the amended IT Rules covering synthetically generated information (SGI). As a detection service, ZSure helps platforms identify and label SGI as required by regulation. Read more in our Privacy Policy.
You can test the detector right now on the Media Verifier. For enterprise access, API keys, or a guided walkthrough of the platform, book a demo with our team.
