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Finding signal on Twitter is more difficult than it used to be. We curate the best tweets on topics like AI, startups, and product development every weekday so you can focus on what matters.
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The checkmarks on a pricing page have no words in them. That one dumb fact is why your AI keeps getting basic questions wrong. Ask an AI which plan comes with a feature, which flight includes a bag, which apartment allows dogs. It answers fast and sounds sure. But most AI tools never look at the page. They run it through a converter that strips everything down to text, and a ✓ or ✗ in a comparison table is an icon, so it just disappears. The cell comes back empty. The model fills in the blank…
Introducing Expand Fetch, a new way to scrape and crawl the web. Your agent has never seen the web. No wonder it gets basic questions wrong. Traditional Markdown APIs lose critical details. So we trained two System one models to change that: Iris, a vision model that sees pages like you do, preserving tables, icons, and layouts. X-Ray, a JSON model that uncovers the hidden data behind every page. Every fetch also comes with a Wayback Machine. Every line links back to its source, so you can verify exactly what your agent saw. Three products. One API. On our benchmark of 1,094 questions across 326 challenging web pages, agents using Expand got 74% right. The next best API got 55%. Available today at $1 per 1,000 fetches. Try it at https://t.co/x4SDYsUX25