Most interview prep has no feedback loop.

Candidates rehearse alone, then walk into the room without knowing which answers were weak.

That is why we built WithIntro around one rule: every spoken answer gets reviewed before the next question.

In the WithIntro case study, users prepared 75% more efficiently.

The AI feedback was the easy part to demo. The harder work was making practice structured enough to measure.

A good practice system helps candidates: → Answer out loud, the way a real interview runs → Read back a transcript of every answer → Get feedback on each answer while it is still fresh → Get the next question based on what was weak → Track their progress from one session to the next

Under the hood: voice capture, Whisper transcription, Claude-powered feedback, adaptive learning paths and an analytics dashboard, built on Next.js and Tailwind.

The best practice tool does not only ask questions. It shows you what to fix before the next one.

At Zenveus, we build the systems behind AI products, so the feature that looks good in a demo keeps working for real users.

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