Automating assessments is easy. Automating trustworthy assessments is the hard part. The moment a test is unproctored and online, some candidates will try to game it, and at hiring volume that is hard to catch by hand.
The three ways an assessment gets gamed
- Impersonation. A stronger friend, or a paid proxy, takes the test on the candidate's behalf.
- Copy-paste. The answer comes from GitHub, a past attempt, or another tab, never from the candidate's own reasoning.
- AI assist. An LLM generates a plausible-looking answer in seconds.
A traditional multiple-choice or take-home test detects none of these. It trusts the submission and moves on. That leaves the screening data hard to trust.
Detection has to be built into the pipeline, not bolted on
Hiearlly's proctoring runs during both assessments and live AI interviews, rather than as a one-off add-on. It watches for:
- A face or voice that doesn't match, and more than one face on screen, to surface impersonation and a second person.
- Other voices in the room.
- Tab switching and copy and paste.
- AI-assist use.
Each event is flagged with a timestamp and rolled into an integrity score that sits beside the candidate's results. A submission that looks perfect on paper but comes with flags is exactly the case a keyword filter can never catch.
The output is timestamped flags and an integrity score, not a verdict. They give the recruiter context, such as “this result is worth a second look”, and Hiearlly never rejects a candidate automatically. A false positive should cost a human a minute of review, not cost someone a job.
Why “advisory, not automatic” matters
Automated rejection on a fraud signal is tempting and wrong. Signals are probabilistic; people are not. A nervous candidate on a slow connection can look, briefly, like a suspicious one. Treating flags and the integrity score as information for your team keeps a human in the loop for the decisions that actually affect a person's livelihood, while still catching the fraud that manual screening misses entirely.
Trust is what makes automation usable
The whole point of automating screening is to act on the results without re-checking them by hand. That only works if you trust the score. Proctoring isn't a feature bolted onto the assessment. It is what makes an automated assessment worth automating in the first place.
Proctoring runs in every assessment and AI interview.