Product Engineering
Scaling Rehearsal AI: Voice Interview Simulations
A case study on building Rehearsal AI, DeepProbe adaptive questioning, and voice-powered AI interview simulations for thousands of candidates.
Problem
Interview prep becomes valuable only when candidates receive specific follow-up questions and credible feedback. Static question banks do not reveal weak reasoning, shallow examples, or vague claims.
System
Rehearsal AI used voice interaction, controlled question delivery, LLM-based answer analysis, and DeepProbe adaptive follow-ups to create a more realistic mock interview loop. The product served 5,000+ candidates across placement and admissions workflows.
Original Write-up
The longer write-up covers the engineering decisions behind scaling voice AI interviews, including question delivery, adaptive probing, feedback quality, and production trade-offs.