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AI Public Speaking Coach � MVP in 11 Days

Voice analysis app that scores clarity, pace, and filler words in real time. Built and launched in 11 days using Next.js and OpenAI Whisper.

11
days to MVP launch
<30s
analysis per speech
$0.02
cost per analysis
?
production-ready

The Challenge

The founder had a clear vision: a mobile-friendly app that lets anyone record a short speech, then receive instant AI feedback on clarity, speaking pace, filler words, and overall confidence. Think of it as a personal speaking coach available 24/7 for a fraction of the cost of human coaching.

The challenge: he had been quoted $80,000�$120,000 and 4�6 months by two dev shops. He needed a production-ready MVP in weeks, not months, and within a budget that let him test with real users before raising capital.

  • Complex real-time audio analysis requirements
  • Budget constraint: needed to test before raising
  • No technical co-founder � needed full-stack delivery
  • Timeline: needed user feedback before investor meetings

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Project Details

Product type
SaaS Web App
Project type
Rapid MVP
Status
Live (Beta)
Build time
11 days
Team size
1 founder + LoopSuit

Tech Stack

Next.js 14 OpenAI Whisper Claude AI Supabase Vercel Cursor AI

The Solution

We scoped, designed, and built the full MVP in 11 days � a production-ready Next.js web app with real-time audio recording, OpenAI Whisper transcription, and a multi-dimensional AI scoring engine.

The Tech Stack

Next.js 14
Full-stack framework, App Router, server actions
OpenAI Whisper
Speech-to-text transcription, filler word detection
Claude AI (Anthropic)
Clarity scoring, coaching feedback generation
Supabase
Auth, database, file storage for recordings
Vercel
Deployment, edge functions, CDN
Cursor AI
AI-assisted development for 3x build speed

Core Features Built

In-browser audio recording � records directly in the browser, no app download required. Works on desktop and mobile.

Real-time transcription � Whisper API transcribes the speech in under 10 seconds, identifying filler words (um, uh, like, you know) with timestamps.

4-dimension scoring � Clarity (word choice, sentence structure), Pace (words per minute vs. optimal), Filler word density, Confidence (assertive language analysis).

AI coaching feedback � Claude generates 3�5 specific, actionable improvement suggestions for each recording. Not generic tips � specific to what was said.

Progress tracking � Historical score dashboard shows improvement over time across all dimensions. Encourages daily practice.

The Results

The MVP launched on Day 11 with 47 beta users. Key outcomes:

  • Zero critical bugs in the first 2 weeks of beta. The tight scope (do one thing really well) meant quality was high from day 1.
  • 4.8/5 average score from beta users on the quality of AI feedback. Users described it as "surprisingly specific" and "better than expected."
  • $0.02 per analysis at scale � well within the economics for a $15�30/month subscription model.
  • Full handoff documentation � code repo, deployment runbook, architecture diagram, and a 45-minute recorded walkthrough for the founder.