Parallel

Parallel (parallel.ai) is an AI infrastructure company that builds web research and search APIs optimized for AI agents—what they call the "web’s second user." Their platform emphasizes accuracy, verifiability, and structured outputs, enabling agents and developers to access reliable web data at scale.

Key Products

• Task API: Provides structured, verifiable answers with citations, excerpts, reasoning chains, and calibrated confidence scores. Supports multiple processor tiers (Base, Core, Pro, Ultra, Parallel 600, Parallel 1200) with increasing accuracy and cost.
• Basis Verification: A built-in framework included in higher tiers of Task API, delivering citations, evidence, and confidence levels for human-in-the-loop workflows.
• Search API: Returns ranked URLs and excerpt-rich, LLM-friendly outputs designed to reduce scraping and improve reasoning.
• Search MCP Server: Wraps the Search API as a plug-and-play Model Context Protocol (MCP) server, giving AI agents high-quality, cost-efficient web search results.
• Source Policy: Lets developers whitelist or blacklist domains to control source reliability.
• Webhooks: Event-driven notifications for completed tasks, making it easy to chain and orchestrate workflows.

Benchmarks & Performance

• Task API: Achieves up to 48% accuracy on BrowseComp/WISER benchmarks, outperforming GPT-4 browsing (1%), Claude (6%), Exa (14%), and Perplexity (8%).
• Search MCP: GPT-4.1 + Parallel MCP achieves 74.9% accuracy at $21 CPM, outperforming native GPT search and Exa.

Parallel is SOC-II Type II certified and focuses on building transparent, evidence-backed infrastructure for AI developers and agents.