Parag Agrawal's Parallel Web Systems hits $2B valuation with AI agents infrastructure raise

Parallel Web Systems hits $2B valuation five months after its last big raise | TechCrunch

Parallel Web Systems, the AI agent-tool startup founded by former Twitter CEO Parag Agrawal, has raised a $100 million Series B at a $2 billion valuation led by Sequoia. Existing investors Kleiner Perkins, Index Ventures, Khosla Ventures, First Round Capital, Spark Capital, and Terrain Capital also participated, the company said. This raise comes just five months after the startup announced its $100 million Series A at a $740 million valuation led by Kleiner and Index, and brings the total capital it raised to $230 million. Parallel offers a suite of web search and research APIs specifically for AI agents and names customers such as Clay, Harvey, Notion, and OpenDoor. It says its customers include banks and hedge funds (though it has not named them). The confidence of investors in Agrawal's startup has to be particularly gratifying for him after his time at Twitter ended with a subsequent lawsuit. Elon Musk famously fired him and all the top execs after he bought Twitter. Those execs, including Agrawal, sued, alleging that Musk failed to pay the $128 million in severance pay they believe they were owed. In October, Musk settled the case for undisclosed terms. In addition to some big-name customers, Parallel tells TechCrunch it has over 100,000 developers using its products.

Parag Agrawal's startup raises $100M to build a parallel web for AI agents - SiliconANGLE

Parag Agrawal's startup raises $100M to build a parallel web for AI agents Former Twitter Inc. Chief Executive Parag Agrawal has raised $100 million to fund his new startup Parallel Web Systems Inc., which is focused on enabling artificial intelligence agents to search the web more efficiently. Sequoia Capital led today's Series B round and was joined by existing investors Kleiner Perkins, Index Ventures and Khosla Ventures, bringing the startup's valuation to $2 billion. Agrawal, who serves as Parallel's founder and CEO, told the Wall Street Journal that his new company will use the funds to establish a sales and marketing team and accelerate its research and development plans. The startup is building a platform that enables autonomous AI agents that perform work on behalf of humans to search the internet for information with much greater accuracy than they do now. It previously raised $100 million in funding in November. Agrawal believes that agents will ultimately "use the web a lot more than humans," and require a different kind of infrastructure to access it properly. More specifically, he said they need the tools to perform "deep research" so they can complete tasks related to insurance claims processing, sorting through government contracts and so on. While humans would use a web browser to do this kind of thing, agents can potentially do it much faster if they have the right tools. Parallel's solution is a programmatic web infrastructure based on a suite of specialized application programming interfaces for searching the internet, performing tasks online, extracting information from websites and monitoring the web. The APIs utilize a proprietary web index that's optimized for "machine retrieval." Agrawal founded the company in early 2024, less than two years after he was forced out of his job at Twitter by Elon Musk, who acquired the social media startup in 2022 before transforming it into X Corp. One of the first companies to use Parallel's tools is the legal AI startup Harvey AI Inc., which has developed autonomous agents designed to perform research-heavy tasks on behalf of lawyers. Harvey co-founder and President Gabe Pereyra told the Journal that it's not enough for agents to just be given access to Google Search. He believes that they require more granular control over which websites they should be accessing, and said that's what Parallel provides. Sequoia partner Andrew Reed said Parallel is providing the core infrastructure needed to support "long-running" AI agents that can operate continuously in the background and maintain context for longer periods of time. "One of the things that is a core shared function amongst all of these long-horizon agents is the ability to use the web," he pointed out. Since launching in early 2024, Parallel has amassed a user base of more than 100,000 developers, including many from AI-native startups and large enterprises, Agrawal said. But Parallel is not the only game in town, with rivals including Tavily Inc. and Exa Labs Inc. also building similar infrastructure to help AI agents navigate the web.

Former Twitter CEO Parag Agrawal's Parallel Web Systems has raised $100 million: WSJ - The Economic Times

Parallel Web Systems, founded by former Twitter CEO Parag Agrawal, has secured $100 million in a Series B funding round led by Sequoia Capital, boosting its valuation to $2 billion.Parallel Web Systems, a California-headquartered startup founded by former Twitter CEO Parag Agrawal has raised $100 million in a Series B funding round, according to a report by the Wall Street Journal on Tuesday. The round was led by Sequoia Capital. Existing investors, including Kleiner Perkins, Index Ventures and Khosla Ventures, also participated. With this round, the startup's valuation has inched up to $2 billion, the report said. The funding comes after the startup raised $100 million in a Series A round last November, valuing the company at $740 million, Reuters reported. Sequoia partner Andrew Reed has joined Parallel Web's board as part of the latest deal. Agarwal said the startup aims to utilise the funds to build out its sales and marketing team and invest in research and development (R&D) initiatives. Founded in 2023, Parallel Web Systems builds application programming interfaces (APIs) that let AI systems search the live web for up-to-date information to complete tasks. AI agents are increasingly being used for complex, research-heavy tasks such as investment analysis, insurance processing, and legal or government data review, performing them faster and at greater scale than humans, noted Agrawal. These "deep research" tasks are traditionally done via web browsers but can now be automated by agents, the founder added.