MiniAiLive

MiniAiLive is a content detector tool. MiniAiLive Face Liveness Detection is a passive 3D anti spoofing SDK for Android, iOS, Linux, Windows and server deployments. It uses texture analysis and optical flow to reject photos, replay videos, masks, avatars and deepfakes during identity checks, aimed at KYC, AML and access control flows.

MiniAiLive Face Liveness Detection is an anti spoofing SDK rather than a consumer app. It equips developers and product teams with a passive 3D liveness layer that runs on live camera input and decides whether the face in frame belongs to a real person or to a photo, replay video, mask, avatar or deepfake. The site frames the tool as a defence for identity flows, pairing biometric matching with presentation attack detection so that a submitted selfie or video cannot be replayed from another source. The engine leans on two mechanisms. Texture analysis looks for the telltale signs of a recaptured image, a projected video or a fabricated face, covering 3D masks, deepfakes and remote-controlled avatars. An optical flow algorithm separates two dimensional objects from genuine three dimensional faces, and a motion trigger captures frames automatically so an attacker has no window to swap or present alternate photos. MiniAiLive states a one second verification time and 99.9 percent accuracy, and notes a patent on the liveness technology. The intended audience is engineering and compliance teams building KYC, AML and access control journeys, particularly in finance and healthcare where sensitive transactions and regulation demand stronger identity proofing. Distribution is through SDKs for Android and iOS with on device processing, plus Linux, Windows and server builds that can be deployed on premises or in the cloud, so a mobile first onboarding flow and an enterprise backend can share the same detection logic. Against alternatives, the differentiator is the passive model: users are not asked to blink, turn their head or follow prompts, which keeps friction low in high volume onboarding. A browser based demo lets a team test sample images and inspect a raw response before committing to an integration. Buyers should treat the accuracy figures as vendor claims, validate performance in poor lighting and weak camera conditions, and confirm commercial terms directly, since pricing is not published on the page.