Qlay offers an AI‑powered proctoring platform for remote technical interviews that detects AI‑assisted cheating. By using a candidate’s smartphone as a secondary camera, the system monitors eye‑gaze and speech cadence to flag suspicious behavior and generates a cheating probability score, helping recruiters ensure authentic assessment results.
Funding
$1.4M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
1ONCFounders
Product
Problem
Remote technical interviews and assessments are vulnerable to AI-assisted cheating, where candidates can use external tools, notes, or generated content to gain an unfair advantage. This undermines hiring decisions, inflates candidate scores, and erodes trust in remote hiring processes.
Solution
Qlay provides an AI-powered proctoring platform that monitors candidates during remote interviews to detect unauthorized assistance. Candidates connect a secondary smartphone camera to capture a side-angle view, allowing the system to verify that no additional devices are present. The platform analyzes eye‑gaze patterns to identify suspicious glances that may indicate reference to external material. It also evaluates speech cadence, pacing, and rhythm to distinguish natural responses from read‑out AI‑generated text. By combining visual and audio cues, Qlay generates a probability score of cheating, enabling hiring teams to make more reliable hiring decisions.
Target Audience
Primary customers are corporate recruiting teams, HR departments, and technical assessment providers that conduct remote coding interviews or skill tests.
Features
- Dual‑camera setup using the candidate’s smartphone as a secondary view to detect hidden devices without special installation
- Real‑time eye‑gaze tracking that flags abnormal eye movements suggestive of reference to unauthorized resources
- Speech cadence analysis that compares candidate’s vocal patterns to natural delivery to spot read‑out or AI‑generated responses
- AI models that integrate visual and audio signals to produce a cheating probability score for each interview session
- Simple web‑based interface for recruiters to review proctoring results and confidence metrics