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Product case study / 0066

0.066

Product Engineer · Event flow and AI systems

An in-person AI speed-dating experience with a browser pipeline that turns noisy-room conversations into a printed compatibility report.

Proof signals

API surface
71 endpoints
Live reach
About 50 participants across live events
AI cost
About $1 per event

User problem

An in-person speed-dating experience needed to capture conversations in a noisy room and turn them into a useful compatibility report.

Ownership

Jaeyong designed the event flow and printed compatibility report, and built the browser pipeline for audio capture and speaker separation.

Selected decisions

  • Designed the event flow around an in-person experience and its printed report.
  • Used Deepgram to separate speakers in noisy-room audio captured in the browser.
  • Routed suitable work to lighter models to keep AI cost at about $1 per event.

Outcome

The system has 71 endpoints, supported about 50 participants across live events, and runs at about $1 in AI cost per event after cost-aware model routing.

Stack

  • React
  • Next.js
  • TypeScript
  • Deepgram