AI interview proctoring software: what works in a live interview

Interview proctoring software checks that a candidate's answers in a remote interview are their own. Most tools sold under that name were built for exams: they lock the browser, watch the webcam or record the screen. In a live video interview, that leaves the biggest gap open, because an AI copilot on a phone or a hidden overlay never touches what they watch.

The useful question isn't "which proctoring tool?" but "what does it watch?" A tool that watches the device can only see that device. A tool that reads the conversation sees the answers themselves, wherever they came from.

What is interview proctoring software?

Interview proctoring software is any tool that helps an interviewer trust that a remote candidate is answering unaided. There are two families: secure-environment tools that control and watch the candidate's computer, and conversation-based tools that read what's said in the call. Exams suit the first. Live interviews need the second.

The trouble is that search results blur them together. Many of the pages that rank for this term describe exam and assessment proctoring (tab switching, ID checks, face tracking) and apply the same toolkit to interviews, as if a timed test and a conversation were the same problem.

Why can't lockdown browsers stop interview copilots?

A lockdown browser controls one browser on one computer. It can't see a phone propped behind the laptop, and it can't see software built to stay out of the screen share. Universities that use one say so plainly: "LDB cannot detect or prevent students from accessing another device, or having someone beside them" (UBC Sauder Teaching Playbook).

Copilots are designed around exactly that blind spot. When CNBC profiled Interview Coder in March 2025, it reported that the tool's website called it "immune to screen detection features" on services like Zoom and Google Meet (CNBC via NBC New York).

So Candit doesn't watch the screen at all. It joins the call, reads the conversation, and flags answers that look AI-assisted live on the interviewer's screen, with the exact line behind each flag and the timing in the AI use report after the call. A copilot can hide its window. The candidate still has to say the answer out loud.

How do the main approaches compare?

The friction matters too. In a 2025 University of Washington study of 16 students with disability accommodations who had sat proctored exams, one participant said: "It just feels like when you're being watched, you can't breathe" (Kwapisz et al., arXiv). It's a small sample of students rather than job candidates, but the point carries over: surveillance costs the honest candidates most.

Which interview proctoring tools use which approach?

Here's where the best-known tools sit, and what each says it uses on its own website.

Device checks see more of one device, but only that device. Capifiq's own site says on-device detection can't see a phone, an earpiece or smart glasses, and handles those with interview questions instead. That's the gap conversation-based detection covers: whatever device the answer came from, the candidate still has to say it. For what "zero friction" should actually mean when vendors claim it, see zero-friction vs secure-environment proctoring.

Vendor details come from each company's own website, checked in October 2026.

What should interview proctoring software actually check?

Good interview proctoring software checks the answers, not the room. Look for four things: nothing for the candidate to install, detection that reads the conversation rather than the screen, evidence behind every flag, and flags that arrive while the interview is still on, early enough to ask a follow-up question.

It should also cope with how copilots try to dodge detection. Many now give the candidate bullet points to put in their own words. That changes the wording, not the shape: a pause while the points appear, then the points delivered in list order, with written phrasing slipping into speech. Candit is built to recognise that format, because it reads the conversation and its timing, not the device.

And ask how the vendor knows it works. Candit's detection is tested by running interview sessions through reverse-engineered builds of common copilots, and retested as they update.

Why does this matter now?

Trust in video interviews is falling. In Checkr's survey of 3,000 US managers involved in hiring, fielded 11–16 September 2026, "Sixty percent say AI has made virtual interviews harder to trust, compared with 51% last year." Only 23% are "extremely confident their hiring process would catch a fraudulent candidate" (Checkr, October 2026).

The response many teams reach for is more surveillance, or a return to in-person rounds. Both add cost and friction, and neither tells you which answer to probe.

Where Candit fits

Candit is zero-friction anti-cheat for hiring: a bot that joins your Zoom, Google Meet, Microsoft Teams, Slack or Webex interview and flags AI-assisted answers live, with nothing for the candidate or interviewer to install. Each flag shows the line that triggered it and a score, per speaker. On paid plans, Counter AI suggests one follow-up question the moment an answer is flagged, and the AI use report shows where AI help showed and how after the call.

A flag is a signal, not a verdict. It tells you which answer is worth probing; the interviewer decides what happens next. See how Zero Friction Proctoring works, or read more on real-time interview proctoring and how to tell if a candidate is using AI in an interview.

Frequently asked questions

Run interviews that hold up

If your team runs interviews over video, the fix doesn't need a new portal or a locked-down laptop. It needs to know which answers to probe while the candidate is still on the call. Book a demo to see AI Detectability in a live interview.