Community networking platform
AI-Driven Content Categorization & Onboarding
Whisper-powered voice onboarding and category matching cut a two-minute manual flow down to about a minute.
- 60s
- category selection, down from 2 min
- 2
- manual flows automated end-to-end
Overview
- Client
- Community networking platform
- Focus areas
- Speech RecognitionNLP
A community platform connecting neighbors for socializing, hiring and trading was losing users during onboarding, as manual profile entry and a clunky multi-level category picker drove drop-off before people ever engaged.
The problem
01
Manual profile creation was slow and error-prone, causing high drop-off during onboarding.
02
Multi-level category selection for requests and offers was cumbersome, hurting engagement and satisfaction.
The solution
The solution
AI-assisted profile creation
Users record a short profile video that's uploaded to Firebase. We run the audio through Whisper to extract name, profession, date of birth, language, gender and marital status, then train a model to auto-fill the profile from that transcript, folded directly into the platform's signup flow.
AI-assisted category matching
The same speech-to-text pipeline powers request/offer creation: a recorded or typed description is matched against predefined categories automatically, replacing the manual multi-level picker entirely.
Results
Profile completion time dropped sharply, with fewer data-entry errors.
Category selection fell from roughly two minutes to about sixty seconds.
Higher onboarding completion and stronger post-signup engagement.
Conclusion
Automating the two most tedious steps in the funnel, profile entry and category selection, turned a source of drop-off into a smoother on-ramp, without asking users to do anything but talk.
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