Hey Product Hunt! 👋

I'm QY, the maker of Aural, and I'm thrilled to finally share what we've been building.

The backstory

Over the past two years, I've conducted 300+ interviews — phone screens, panel interviews, case studies, technical deep-dives — across consulting, tech, and startups. Before that, I spent years at McKinsey leading AI transformation projects and built ML systems at Uber in San Francisco. Through all of it, the same problems kept showing up:

Senior people spending half their week in back-to-back interviews instead of doing their actual work
The same questions asked hundreds of times, the same answers given in the same order
40-minute conversations reduced to three bullet points and a vague "strong hire" recommendation
Hiring decisions that ultimately came down to gut feelings — strong candidates rejected because the interviewer was tired at 4 PM

After the first hundred interviews, the pattern was impossible to ignore. After three hundred, I couldn't walk away from it.

What we built

Aural is an AI-powered interview platform that conducts real, adaptive conversations — through chat, voice, or video. You describe what you want to learn, the AI generates an interview structure, and participants join through a simple link. The AI listens, follows up intelligently, and adapts its depth and tone in real time — just like a skilled human interviewer.

Every session automatically produces transcripts, competency scores, key insights, and exportable structured data. No more hours of manual note-taking or comparing scribbled notes across interviewers.

Key features

Three modes: chat, voice, and video, all powered by the same adaptive AI engine
Real-time adaptation: adjusts follow-up depth and direction based on what the participant actually says
Smart question types: open-ended, multiple choice, rating scales, coding challenges, and whiteboard
Instant analysis: AI-generated summaries, competency scores, theme detection, and data export (Excel/PDF)
Anti-cheating mode: tab-switch tracking, paste blocking, multi-monitor detection for high-stakes assessments
Set up in minutes: describe your goal in plain language, share a link, get insights

Who it's for

We designed Aural to be flexible across use cases:

Hiring teams: screen candidates at scale with consistent, structured interviews
Mock interviews: practice for technical, behavioral, case, and system design interviews with AI coaching and real-time feedback
User research: conduct discovery interviews at scale with context-aware follow-ups
Customer discovery: validate product ideas through structured conversations
Feedback collection: gather insights from customers, employees, or event attendees
Academic viva: thesis defense prep and oral exam practice

One thing that surprised us: candidates are often more honest with AI. Without the social pressure of impressing a human interviewer, people give more candid answers, admit what they don't know, and explain their real thought process. This actually produces better data for decisions.

Where we are

Aural is live with a free tier — no credit card required. We're a small team with strong opinions about how interviews should work, and we're building toward a future where every candidate gets a fair, structured, and thoughtful experience.

I'd love your feedback on:

Which use case resonates most with you?
How does the voice/video experience feel?
What integrations would make Aural fit your workflow?

Your feedback directly shapes our roadmap. Try it out, drop a comment, or just say hi — I read every single one. 🙏