Parallel Secures $100 Million to Reimagine the Web for AI Agents
New funding at a $740 million valuation strengthens the startup founded by former Twitter CEO Parag Agrawal as it pushes to build machine-first web infrastructure for AI agents.
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Parallel Web Systems, founded by former Twitter CEO Parag Agrawal, has raised $100 million in its latest funding round at a valuation of $740 million.
The Palo Alto–based firm, which builds web infrastructure for AI agents, said in a blog that the round was co-led by Kleiner Perkins and Index Ventures, with participation from Spark Capital and existing investors Khosla Ventures, First Round Capital and Terrain.
With the new capital and a growing roster of enterprise customers, Parallel plans to strengthen its agent-friendly web APIs, expand its technical capabilities and build a community focused on keeping the web open and accessible for AI-driven innovation.
Founded in 2023, Parallel had previously raised about $30 million from Khosla Ventures, Index Ventures and First Round Capital.
In a LinkedIn post on Wednesday, Agrawal wrote, “We have raised $100 million A to build the web for its second user,” adding that the round was led by Kleiner Perkins and Index, with Spark and existing investors Khosla, First Round and Terrain also participating.
The funding underscores investor confidence in Parallel’s vision. Kleiner Perkins partner Mamoon Hamid will join Vinod Khosla, Shardul Shah and Josh Kopelman on the company’s board.
Parallel’s technology is used by Fortune 100 companies and fast-growing startups including Clay, Sourcegraph, Owner, Starbridge and Genpact.
As more businesses adopt AI, the company aims to provide the underlying infrastructure for agent intelligence on the web. Its founders, who have experience building large-scale web systems, see Parallel as laying the groundwork for an AI-centric web.
While some argue that large language models could make traditional web search obsolete for agents, Parallel believes AI systems will increasingly rely on high-quality, real-time web data to gain an edge in decision-making and workflow automation.
Parallel’s platform offers two types of products to help AI agents get better data: Web Tools and Web Agents.
Web Agents support deeper, structured research and automate complex tasks such as discovering government RFPs, searching legal precedents and underwriting insurance claims.
In its latest blog post, the company said it aims to support an open and competitive web ecosystem at a time when human attention is declining and privacy concerns are rising.
It argues that while older web systems were built to maximize clicks, its infrastructure is designed for AIs at scale by improving crawling, caching and context-rich retrieval.
Parallel has also configured its APIs to encourage data owners and publishers to keep content open, supporting agent access and a healthier web economy.
