Parallel is a web infrastructure platform built specifically for AI agents and the products that embed them. Instead of stitching together search engines, crawlers, and scrapers, developers get a single API for searching the live web, extracting page content, running deep research, monitoring changes, and enriching datasets — with every output carrying citations and calibrated confidence scores so results can be trusted in production.
At the core of Parallel is its proprietary Web Index, a continuously updated index covering hundreds of billions of pages, ranked for authority and freshness and including licensed sources such as paywalled publishers and premium newsletters that other indexes do not have. On top of that index sit two layers: Web Tools, the raw search and extraction primitives, and Web Agents, specialized research agents that plan a question, search across dense sources, and return structured, cited answers. The platform is already used by more than 1,000 teams, from AI startups to Fortune 500 enterprises, including Notion, Harvey, Granola, Pfizer, and Replit.
Parallel follows usage-based pricing with a free starting allowance — new users receive a monthly free credit ($5 per month) before per-request paid pricing applies, and enterprise tiers add licensed content and support. It is best classed as Freemium: developers can start for free and pay as agent traffic grows.
Parallel suits AI product teams, agent builders, and data-driven companies that need current, verifiable web facts inside their product — from copilots answering with live sources, to sales and investment teams automating account research, to platforms monitoring competitors, pricing, and regulation at scale.