Build structured web datasets
Riveter turns web research into structured data. Give Claude a list of companies, people, or URLs and ask for new columns: product descriptions, revenue, deep analysis, company headcount, link traces, pricing, tech stack analysis, contact details, a classification, a summary, etc. Riveter runs an AI agent per row that searches, reads pages, and fills in each cell with a sourced answer. What you can do - Enrich rows you already have. Paste a list or point at a saved enrichment and get the new columns back. Up to 10,000 rows per run. - Build a list from a description. "Every lawfirm in Indiana", "every YC W24 company in healthcare", "competitors of Stripe". Riveter generates the rows, and can enrich them in the same run. - Scrape a page. Clean text or markdown from any URL, including JavaScript-rendered pages. - Search the web. One-shot search results, or a research agent that answers a question with a structured, schema-shaped response. - Extract records from a site. Define the fields you want and pull them from listings, directories, or catalogs as JSON. - Monitor for changes. Run a saved enrichment daily, weekly, or monthly and get alerts or webhooks when values change. How it works Long runs are asynchronous. Claude starts the run, checks status, and fetches results when they are ready. Every run has an id you can come back to later, and results stay available in your Riveter account.
When connected to Riveter, ChatGPT may share relevant chats and memories with this app to help provide context for your requests. Riveter’s use of this data is subject to their terms and privacy policy. If you have Memory enabled, data from the app may be used to proactively provide helpful information or suggestions. ChatGPT always respects your training data preferences, including for data from connected apps. Use of apps may come with elevated risk. You can manage your preferences or disconnect from apps anytime in your settings. Learn more