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View technical comparison →Riveter AI, Inc v1.0.1
Build structured web datasets
Developer declarations; not independently tested. Listing last checked Nov 4, 2026. Package observed Nov 3, 2026.
Not specified in the available declarations: capabilities, limitations, pricing & account requirements.
Build a list of 25 US B2B SaaS companies founded since 2020 with their website, HQ city, and CEO.
From the marketplace listing
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.
Language: English · Automatically detected from descriptions.
Exact text from the indicated source. A mention alone does not establish support for your task.
app-6a98d577cb1881919b34b0af0d6240c5
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.
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Publisher declarations from the archived package. These are separate from our research and the live service's terms.
Package observed Nov 3, 2026.
plugin_asdk_app_6a98d577cb1881919b34b0af0d6240c5
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