AI Interviewer
Automated qualitative research that delivers deep user insights in minutes instead of weeks — with psychometric profiling baked in.
The Problem
A single round of qualitative user research costs $5–15K, takes 2–4 weeks, and most product teams skip it entirely because of that. The ones who do it get 6–8 interviews and call it a day. The insights decay before they're even acted on.
The Approach
Multi-agent orchestration where one agent conducts the interview — adapting questions in real-time based on responses — while another synthesizes insights with Big Five and Enneagram psychometric profiling. The interview agent doesn't follow a rigid script; it probes deeper when it detects surface-level answers and pivots when a new theme emerges.
I integrated Beyond Presence for avatar-based conversations (people open up more to a face than a chatbox) and Phoenix observability to trace every LLM decision for quality control.
The Result
90% cost reduction compared to traditional interviews. Minutes instead of weeks for synthesized insights. Scalable concurrent interview capacity — run 50 interviews simultaneously, something no human team can do.
My Role
Product lead and builder at ProductLoop. Designed the research methodology, built the agent pipeline, integrated real-time voice, and made the product decisions around when AI should probe deeper vs. move on.