AI Interview Glossary

TalentLyt's comprehensive integrity stack that analyzes 13 distinct signal types—including lip-sync, voice biometrics, and gaze tracking—to ensure absolute session authenticity.

An AI interview technique where follow-up questions are dynamically generated based on the candidate's previous responses, allowing for deeper exploration of relevant topics.

A software solution that uses artificial intelligence to conduct, evaluate, and/or verify job interviews. These platforms automate various aspects of the interview process while maintaining assessment quality.

The process of monitoring and analyzing a candidate's behavior patterns during an interview, including typing speed, response timing, and interaction patterns to detect anomalies.

A feature that records and replays how a candidate wrote their code during a technical interview, showing the entire development process rather than just the final result.

AI analysis of how a candidate approaches problems, their vocabulary usage, and thinking patterns to verify consistency and detect potential fraud.

In multi-agent AI systems, the requirement that multiple AI agents must agree on an assessment before it is finalized, reducing errors and increasing accuracy.

A specialized AI component that monitors interview sessions for signs of fraud, cheating, or misrepresentation. TalentLyt's Forensic Engine works alongside Maya to verify integrity.

Technology that monitors where a candidate is looking during an interview to detect if they are reading from notes, a second screen, or receiving off-camera assistance.

The process of ensuring that an interview candidate is authentic and completing assessments without unauthorized assistance, including proxy detection and fraud prevention.

A portable, cryptographically-signed record of a candidate's verified skills and interview performance. A portable intelligence standard for engineering hiring that travels with the candidate.

Analysis of typing patterns, speed, and rhythm to detect anomalies like copy-paste events, AI-generated responses, or multiple users working on the same session.

A Core Web Vitals metric measuring how long it takes for the largest content element to load. Important for SEO and user experience on interview platform pages.

TalentLyt's conversational AI agent that conducts adaptive technical interviews, asking questions and evaluating responses with natural, human-like conversation.

An AI architecture where multiple specialized agents work together on a task. In interviews, different agents handle conversation, integrity verification, and technical assessment.

An ML-driven model that analyzes interview performance and behavioral signals to predict a candidate's likelihood of success in a specific role with 85% accuracy.

A person who fraudulently takes an interview on behalf of another candidate. Detecting proxy actors is a key function of interview integrity verification systems.

TalentLyt's multi-layered integrity verification architecture that includes Vision-Sync and Cognitive-Audit systems working together to ensure interview authenticity.

An interview format where all candidates are asked the same core questions in the same order, providing a standardized comparison baseline and reducing bias.

The process of evaluating a candidate's technical skills, usually through coding challenges, system design questions, or technical discussions.

Implicit preferences or prejudices that affect hiring decisions without the interviewer's awareness. AI interview platforms can help reduce unconscious bias through standardized evaluation.

TalentLyt's multi-modal monitoring system that synchronizes video, audio, and behavioral data to create a comprehensive view of the interview session.