Most “lead tools” tap out after 1 suburb or a handful of results. And if you try to scale? You either hit Google’s API limits… or your wallet takes the L. $5 here, $12 there — just to scrape data that’s already public. So I stopped relying on APIs. Stopped buying databases. Stopped praying someone else did the scraping right. And I built this instead 👇 ✅ Enter a business type (like "plumber" or "dentist") ✅ Enter a city (like "Los Angeles") ✅ The system auto-generates 30+ hyper-local Google Maps search terms: • plumber+in+hollywood • plumber+in+echo+park • plumber+in+downtown • plumber+near+koreatown • ...it goes deep. Like, “every-corner-of-the-city” deep. Then it gets to work: — Scrapes websites from Google Maps — Filters out junk & Google-owned links — Deduplicates and cleans the list — Extracts valid emails from the homepages using Regex — Delivers a clean sheet of contacts and sites No scraping headaches. No wasted API credits. No manual copy-paste ever again. Perfect if you sell: → Web design → SEO → Paid ads → Local services → B2B outreach to SMBs Basically, if your ideal client is on Google Maps... this system turns their map pin into a real lead. I’ve used it to pull 1,000+ niche businesses per city. No limits. No bloat.

While everyone debated chatbots…Sarvam AI focused on documents. And that focus matters. Recent benchmarks suggest the Sarvam Vision OCR model outperforming ChatGPT and Gemini on Indian language OCR tasks — especially on low-quality scans and real-world documents. >Why This Is Important India doesn’t run on clean PDFs. We deal with: - Blurry mobile scans - Government forms - Aadhaar copies - Regional-language invoices - Mixed Hindi + English documents Sarvam Vision is built for: - Indian languages & scripts - Noisy, real-world formats - Enterprise & public-sector workflows - Bharat-scale document processing >What This Means for Builders If you're using n8n, Power Automate, or Make, this unlocks: ✅ Hindi doc → OCR → JSON → database ✅ GST invoice → extract → auto-validate ✅ Land records → digitize → searchable Instead of making global models fit India,you use a model built for India. That means higher accuracy, fewer corrections, and more reliable automation. Sometimes the advantage isn’t being the biggest model. It’s being the most relevant one. What’s your take — will India-first AI dominate applied workflows? 👇