Parallel Web Systems builds web infrastructure for AI agents. Its APIs let software search the web, extract page contents, monitor changes and run deep research, returning cited, structured outputs that production systems can trust. The Search API returns ranked URLs with compressed excerpts, Extract pulls full page content, Task handles deep research and data enrichment, Monitor sends alerts on new events, and Find All builds datasets of entities matching a query. Pricing is pay as you go, with up to 5,000 requests per month free and per-request costs from $0.001 to $2.4.
Parallel serves developers and companies building agents, assistants and research products that need fresh facts beyond a model's training data. Startups and enterprises in finance, life sciences, sales, insurance, legal and productivity use it, and security is covered by SOC 2. Engineers wiring up a search tool call care about latency, with Search responding in 200 milliseconds to 3 seconds, while analysts and operations teams rely on asynchronous research that returns analyst-grade reports. Developers can begin on the free tier and scale as usage grows.
Common uses include monitoring portfolio companies, competitor pricing and regulations, or watching clinical trial registries and FDA updates for a target indication. Teams give an assistant current answers to questions like what changed in the EU AI Act this month, generate hundreds of cited account briefs or investment memos in minutes, and enrich lists of companies with headcount and funding data pushed into a CRM. Every enriched field carries citations and a confidence score. The Responses API provides cited answers in seconds and is compatible with existing chat-completion style clients.
