If you have heard the phrase "interview intelligence" three times this year and still cannot define it, you are not alone. The term is everywhere and nobody agrees on it. Here is the working definition that holds up.
Interview intelligence is the practice of treating every interview as a data point that compounds. A single interview produces feedback for one hiring decision. A thousand interviews, captured and structured, produce a map of how your company actually hires.
The map shows things you cannot see otherwise. Which interviewers are aligned with each other. Which skills your rubric claims to assess versus which skills your interviewers actually ask about. Which candidates were rejected for reasons that contradict their interview evidence. Which questions predict performance on the job.
Notetaking tools are not interview intelligence. A transcript is raw material. Intelligence is what happens when you connect transcripts across interviews, candidates, roles, and time. Most "AI notetakers" stop at the transcript and call it a product.
A 280 person tech team in Asia ran their interviews on Excel sheets and Google Forms for years. One line feedback. "Good at DS, good at system design." No connective tissue between rounds. They had 1,300 candidate records and zero institutional knowledge. That is the absence of interview intelligence.
The presence of it looks different. A recruiter at a $4.5B company cloned a senior product manager scorecard in 10 minutes by pointing the system at 24 prior interviews for the role. The intake call became optional because the data already knew what the team valued.
Mazle was built around this idea. The Cortex layer is what makes interview data compound. Without compounding, you have notes. With it, you have a hiring brain.
