AI product
TRACE is an open weekly benchmark of web-scraping APIs used to retrieve pages for AI agents. It tests context.dev, Exa, Firecrawl, and Keenable on a fresh sample of roughly 2,500 web pages each week, measuring page-access rates, latency percentiles, returned-content quality, cost per page, and failure reasons. The sample pipeline discovers URLs from publisher feeds, job boards, regulatory listings, filings, legislation, research sources, sitemaps, Wikipedia edits, and other public sources; freezes the sample with caching disabled; and uses a blind judge to evaluate provider responses. It publishes results by source and category, confidence intervals, page-level data, sample history, methodology, and source code, retaining prior grades when scoring rules change.
1 use taken from transcripts — each links to the moment in the video.
An open weekly benchmark that tests how reliably web scraping APIs read pages for AI agents, sending about 2,500 fresh pages weekly to providers like context.dev, Firecrawl and Conneal with caching off and reporting access rate, speed and cost per page. Data and code are public.
1 in the library.