From AI scraping to AI matching — building the data pipeline for competitive analysis
AI scraping collects cleaner data than rule-based crawlers. AI matching processes it beyond what string comparisons allow. Here is how the full stack works.
Marketplace data deduplication: cleaning scraped listings at scale
Scraped marketplace data is full of duplicate listings — different sellers, different titles, same underlying product. AI-powered deduplication collapses these into canonical records for reliable analytics and catalog management.
Lead enrichment through data matching: combining scraped and CRM data
Your CRM has 50K contacts with gaps. Scraped conference lists, directories, and profiles have the missing data. AI-powered matching connects records across sources — even when names, titles, and company names don't match exactly.
Building competitive intelligence from scraped data with record matching
Scraped data from multiple platforms contains the same entities represented differently. AI-powered record matching connects job postings, product listings, reviews, and properties across sources to build a unified competitive intelligence picture.
From web scraping to price intelligence: matching products across competing sites
Scraped product data from competitor sites uses different naming conventions, SKU systems, and category structures. AI-powered matching connects equivalent products across sources to build real-time competitive pricing intelligence.