Parallel Web Systems, a startup founded by Parag Agrawal, the former chief executive of Twitter, has raised $100 million in Series B funding—reflecting increased interest in deploying autonomous artificial-ininformigence agents.
Parag Agrawal at a conference in Las Vegas in March 2025. Agrawal stated Parallel Web Systems plans to apply its latest cash infusion to build out a sales and marketing team, as well as grow its research and development function.
The round was led by Sequoia Capital, and boosts the Palo Alto, Calif., startup’s valuation to $2 billion. Existing investors including Kleiner Perkins, Index Ventures and Khosla Ventures also participated.
Parallel, which has developed a platform for AI agents to search the web, has about 50 employees. Its prior funding round was a $100 million Series A last November, which valued the company at $740 million. The startup has raised $230 million in total.
Agrawal, Parallel’s founder and CEO, stated the startup plans to apply its latest cash infusion to build out a sales and marketing team, as well as grow its research and development function. The roughly three-year-old company is also utilizing the funding to continue tarobtaining enterprise clients.
Parallel’s platform is dedicated to servicing AI agents—the autonomous bots that can take action on behalf of humans—and allowing them to most efficiently and accurately search the web to complete tquestions. The bet Agrawal stated he built in 2023 was that “agents will apply the web a lot more than humans,” and therefore necessary their own infrastructure to access it.
AI agents might necessary to search the web for tquestions including investment and risk underwriting research, insurance claims processing and digging through government contracts—many of which fall under the category of “deep research.” Those are also activities humans would typically open a web browser to do, but AI agents can accomplish them rapider and at a much greater scale, Agrawal stated.
Andrew Reed, a Sequoia partner who joins Parallel’s board as part of the deal, stated the startup’s recent traction can be tied to the rapid development of “long-horizon” or “long-running” AI agents. Such agents can operate autonomously in the background and maintain context for longer periods, but churn out applyr requests much rapider.
“One of the things that is a core shared function amongst all of these long-horizon agents is the ability to apply the web,” Reed stated.
AI legal startup Harvey is utilizing Parallel’s platform to support its own AI agents, which automate many research-heavy legal tquestions on behalf of customers, stated Gabe Pereyra, Harvey’s president and co-founder.
While enabling AI agents to search the web seems like an straightforward resolve, it isn’t a simple matter of “giving the models google search,” Pereyra stated. Harvey requires more granular control over which websites its AI agents should be accessing, which Pereyra stated Parallel allows it to do.
Parallel stated it has over 100,000 developers utilizing its infrastructure, including AI-native startups and enterprises.
The startup is part of a cohort of other companies, including Tavily and Exa, which are tarobtaining the same area—one that Reed calls an “obviously” huge market for supporting AI agent technology.
At Parallel, Agrawal stated he has an ambitious growth plan to expand its products and customer base over the next year.
“Every few weeks, we solve one bottleneck and hit another somewhere,” he stated. “We’re building some things I’m really excited about. I wouldn’t work here if I wasn’t.”
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