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AI & Data Engineering Case Study

Automating B2B Lead Scraping & AI Qualification Pipeline

How Qodes built a distributed web scraping and AI enrichment platform that extracted, sanitized, and classified 10,000+ local commercial businesses with verified phone numbers and decision-maker profiles.

10,000+
Leads Extracted
98.2%
Data Accuracy
82%
Cost Reduction
14 Days
Delivery Time

1. The Problem

The client's sales team was spending 30+ hours weekly manually searching directories, copy-pasting contact details, and calling disconnected numbers. Expensive databases like Apollo and ZoomInfo lacked deep coverage of local brick-and-mortar SMBs.

2. The Solution by Qodes

  • Geospatial Scraping Engine: Built Python-based multi-worker scraper querying OpenStreetMap, Google Places, and local business registries in parallel.
  • AI Entity Extraction: Integrated lightweight LLM prompts to sanitize unstructured business titles, determine decision-maker names, and flag high-intent sales signals.
  • Automated WhatsApp CRM Integration: Direct webhook pipe pushing verified prospects straight into the sales rep dashboard.

3. The Impact

Within the first month of deployment, the client sourced over 10,000 verified leads at an 82% lower cost than commercial lead databases, enabling their outbound sales team to triple monthly pipeline revenue.

Want to Automate Your Business Workflows with AI?

Discuss custom AI agents, web scrapers, and automated pipelines directly with Founder Lokesh Tripathi.

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