Cybersecurity Approach
identifAI approaches generative AI risks as a cybersecurity problem, not as a static ML classification task.
This has three concrete implications that materially differentiate identifAI from established players:
De-Generative Models
Our core technology, the "De-Generative Model", is an AI system designed not to create, but to critically analyse. Its function is to forensically examine digital media—images, video, and audio—to distinguish between authentic and synthetically generated content.
Each modality is processed by a specialised model. For video files, our system executes a comprehensive pipeline: the asset is separated into frames and audio, each is independently scrutinised, and a heuristic engine then produces a final, holistic assessment.
Detects fully AI-generated images and video. Built for KYC onboarding, content verification and fraud prevention. Processes millions of assets daily at sub-half-second speed.
The FACE version detects face-swapped selfies, synthetic avatars and camera injection attacks at point of submission. Built to protect identity verification and onboarding flows.
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Detects cloned and synthetic voice in live calls and recordings. Sub-half-second. No perceptible latency. Built for telecoms, call centres and enterprise.
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