Impersonation
A stand-in sits the interview in place of the real candidate.
VivaGuard confirms the enrolled candidate is the one answering, and flags read-aloud or AI-generated answers. It runs entirely on your servers. No candidate audio ever leaves.
“We could never really tell who was answering. Was it AI, a friend standing in, or the candidate reading out AI-generated answers? VivaGuard confirms the enrolled candidate is the one speaking and flags answers that are being read rather than genuinely spoken. And it all runs on our own infrastructure, so no candidate audio ever leaves our environment. We wired it in with a simple API in a few days, and it indeed has strengthened our trust layer.”
Webcams and honor codes don't catch fraud that happens through the microphone, by someone who isn't the candidate, or who isn't really answering.
A stand-in sits the interview in place of the real candidate.
The candidate reads a pre-written or ChatGPT answer aloud instead of thinking.
A helper off-camera feeds lines the candidate simply repeats.
Video watches the screen and room, not who is speaking, or how.
Is this really the enrolled person, and are they genuinely answering? Three steps, in order.
The candidate reads a random sentence in a short, timed window, a liveness step that captures a genuine, live reference voice.
Any later recording is matched against the enrolled voiceprint. Same person or not, with a clear accept/reject and a similarity score.
Scores speech naturalness (disfluencies, pauses, pacing) to tell genuine thinking-aloud from a read or fed answer.
Voiceprint matching plus speech-naturalness analysis, catching stand-ins, read-aloud, and coached answers.
No audio, transcript, or result ever leaves. Zero third-party calls, zero per-call cost.
Docker, CPU-only, fully air-gapped after setup.
Three endpoints and a built-in console. Drop it into any interview or exam workflow.
See VivaGuard run on your own infrastructure. No candidate data leaves your servers.
Book a demoVivaGuard checks two things about every spoken answer in a remote exam or interview. First, whether the person speaking is the candidate who enrolled, using speaker verification against a live reference sample. Second, whether the answer is genuinely spoken rather than read aloud, using speech-naturalness analysis of disfluencies, pauses, and pacing.
Impersonation, where a stand-in sits the interview in place of the real candidate. Reading AI-generated or pre-written answers aloud. Off-mic coaching, where a helper off camera feeds lines the candidate repeats. Conventional video proctoring watches the screen and the room, not who is speaking or how.
No. VivaGuard runs entirely on your own infrastructure. No audio, transcript, or result leaves your environment, which makes it suitable for institutions with data residency obligations under regimes such as the EU GDPR and India's DPDP Act.
VivaGuard ships as a Docker deployment that runs on CPU only and is fully air-gapped after setup. It exposes a REST API with three endpoints and a built-in console, so it can be wired into an existing interview or examination workflow rather than replacing it.
Video proctoring watches the room and the screen through a webcam, so it detects a second face, a glance away, or a change of window. It does not analyse who is speaking or how the answer is delivered. Speaker verification answers the identity question directly, and speech-naturalness analysis answers whether the candidate authored the answer.