Former Twitter CEO Parag Agrawal has taken a major step forward in the artificial intelligence industry with his startup, Parallel Web Systems, successfully raising $100 million in Series A funding. This achievement, confirmed by a Reuters report, marks a significant expansion of the company’s mission to reshape how AI agents interact with live online information. The funding round places the company’s valuation at an impressive $740 million, highlighting the strong confidence investors have in its vision.

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Parallel Web Systems was founded with a goal that goes beyond traditional search technology. Instead of focusing on human-centered search, the company is developing infrastructure that allows AI agents to access real-time, high-accuracy online information. These agents function as intelligent digital tools capable of performing complex tasks autonomously. Agrawal describes his mission as creating a new internet layer built specifically for machine use, enabling AI to retrieve information more efficiently than the standard web allows.

The Series A funding round was led by prominent venture capital firms Kleiner Perkins and Index Ventures, with continued support from earlier investors such as Khosla Ventures. This investment follows the startup’s earlier seed round of $30 million raised in January 2024, bringing its total funding to $130 million. With this new capital, the company plans to scale its engineering team, strengthen its technology infrastructure, and develop licensing partnerships that will allow legal access to valuable online content for AI use.

Agrawal’s move into AI search aligns with a larger industry trend in which autonomous AI systems are becoming central to digital operations. Traditional search engines are designed to serve humans, but modern AI requires real-time, machine-optimized information to function at its highest potential. Parallel Web Systems aims to bridge this gap by enabling AI agents to conduct live web searches and gather information without depending on human prompts.

The technology developed by Parallel Web Systems is already being used by enterprise clients looking to enhance their internal AI capabilities. Companies are relying on this infrastructure to streamline workflows, improve decision-making processes, and access rapidly updated online content. The startup’s machine-first approach positions it as a foundational technology for industries like healthcare, finance, logistics, and research, where accuracy and speed are essential.

As AI systems continue to evolve, the demand for machine-optimized data retrieval will only grow. Parallel Web Systems is positioning itself at the forefront of this transformation by offering a platform designed specifically for autonomous digital operations. With strong investor backing and a clear technological direction, the company is prepared to shape the future of AI-powered search and redefine how machines interact with the internet.