Research and best practices on interview integrity, AI-assisted fraud detection, and building hiring processes you can defend.
There is no single tool that catches every form of interview fraud. The landscape is fragmented by use case — exam proctoring, coding integrity, behavioral scoring, post-interview analysis. An honest guide to what each category actually does.
Proctoring was built for standardized exams with fixed answers and known rubrics. Job interviews are structurally different. Here's why live monitoring misses most interview fraud — and what catches it instead.
Earpieces, second screens, and real-time AI feeds are harder to catch than a substitute candidate — because the person on camera is genuinely there. Here are the behavioral signals that give it away.
AI-assisted answers don't look like cheating. That's the problem. Here are the behavioral signals that give it away — and why spotting them manually doesn't scale.
A candidate performs well, passes every round, and impresses the whole team. The person who shows up on day one is noticeably different. Here's how it works — and what actually catches it.
When your interviewer is an AI, the signals that catch dishonesty don't show up in the transcript. They show up in the recording. Here's how to think about integrity across the full stack.