Automated collection of publicly available web data at scale - pricing, listings, hiring, reviews - turned into structured datasets.
Web scraping is the automated extraction of data from public web sources. At the scale a data provider operates, it is less about a single script and more about running a resilient fleet: headless browsers that render JavaScript, rotating proxies to avoid single-IP throttling, and respect for each site's rate limits and terms. The output is a live view of activity - prices, product availability, job postings, reviews - as it changes.
The engineering difficulty is rarely the first fetch; it is staying correct over time. Pages change their layout without warning, anti-bot measures evolve, and a selector that worked yesterday silently returns nothing today, so a scraping system needs monitoring that catches a source going quietly empty. Once collected, the raw HTML is worthless until it is parsed into a consistent schema, deduplicated, and normalized - which is where most of the real value is added.
A live evaluation measures EdgeOrigin against your coverage requirements: decision-ready real-time data, delivery latency into your systems, and record-level provenance.