## Inspiration
Sales teams spend 3-4 hours daily copying business data from Google Maps into spreadsheets. We wanted to automate this entire workflow with AI.
## What it does
GMapsScraper AI extracts structured business data from Google Maps. Users enter a business category and location, and receive 200+ results with names, phone numbers, emails, websites, addresses, ratings, and reviews in under 30 seconds.
## How we built it
- Frontend: Next.js with multi-language support (18 languages)
- Backend: Go-based scraper running on Google Cloud Run
- Database: Supabase for auth and user management
- Deployment: Cloudflare Workers for global edge delivery
- AI Layer: Data enrichment and validation pipeline
## Challenges we ran into
- Google Maps rate limiting and anti-bot detection
- Normalizing address formats across 18 languages
- Building a credit system that handles concurrent requests safely
## What we learned
- AI-powered data validation significantly improves extraction accuracy
- Credit-based pricing converts better than subscriptions for this use case
- Multilingual SEO drives more organic growth than paid ads
## What's next
- Direct CRM API integration (HubSpot, Salesforce)
- Email enrichment built into the extraction pipeline
- Chrome extension for in-page extraction
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