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Pay-per-request web search, extraction, and deep-research APIs built for AI agents, not humans
Parallel builds APIs that let AI agents search, extract, and reason over the web instead of scraping pages themselves: a Search API returns ranked URLs and excerpts, an Extract API converts a public URL into clean markdown, a Task API runs deep research with citations and a confidence score, and a Monitor API tracks pages continuously and fires webhooks on changes. It is priced per request rather than per token, starting around $1 per 1,000 search requests, with a recurring free monthly allowance on every account. The company, Parallel Web Systems, was founded in 2023 by former Twitter CEO Parag Agrawal and Travers Nisbet, is based in Palo Alto, California, and had raised a $100 million Series B at a $2 billion valuation as of its most recent funding round. Named customers include Harvey, Notion, and Dropbox.
Search API starts around $1 per 1,000 requests (about $0.001/request); every account also gets a recurring free monthly allowance of $5, roughly 5,000 requests.
Use tool ↗Parallel is infrastructure, not a consumer product: it gives AI agents a way to search and pull clean web content without each team building its own scraper and rate-limit handling. The per-request pricing and named enterprise customers (Harvey, Notion, Dropbox) suggest it is built for production agent workloads rather than hobby projects, and the size of its funding points to a well-resourced, fast-growing vendor.
Watch out: This is developer infrastructure billed per request - it is not a consumer research tool you would use directly in a browser.
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