Parallel
Web infrastructure APIs that let AI agents search, extract, monitor and research the live web with citations.
Visit Website ↗Parallel is web infrastructure built for AI agents, offering APIs to search, extract, monitor and research real-time web information. It runs its own web-scale index of billions of pages updated daily, so agents get current data instead of stale training knowledge.
Its APIs include Search (ranked URLs and excerpts), Extract (turning PDF- and JavaScript-heavy pages into clean markdown), Task (deep research and enrichment with citations and confidence scores), Monitor (webhook alerts on changes) and FindAll (building datasets from natural language). The Basis framework adds calibrated confidence scores, citations and reasoning traces for production trust. It fits high-accuracy work like finance, legal and competitive intelligence.
Key Features
- Own web index of billions of pages, updated daily
- Search API returns ranked URLs and excerpts
- Extract API turns PDF/JS pages into clean markdown
- Task API for deep research with citations
- Monitor and FindAll for change tracking and datasets
Pros
- Priced per request, not per token
- Citations and confidence scores build trust
- Composable APIs for different needs
Cons
- Developer-facing, not an end-user tool
- Advanced usage is paid
Use Cases
- Giving agents live web search
- Extracting clean structured data from pages
- Automating competitive and investment research
Editor's Note
把「給代理用的網路層」做得很完整，附引用與信心分數這點對高正確性場景很關鍵。
FAQ
Who is Parallel for?
Developers and companies building AI agents that need current, citable web information.
How is it priced?
Per request (not per token); search starts at $1 per 1,000 requests, with a $5 monthly free allowance for new accounts.
How is it different from a normal search API?
It runs its own index and adds citations and confidence scores for accuracy-critical work.