Parag Agrawal, the former CEO of Twitter (now X), today officially launched Parallel Web Systems Inc., a forward-looking artificial intelligence startup with a bold mission: to build the Internet for AI agents. Backed by a substantial $30 million in funding, the company is poised to transform how machines interact with the web, redefining the architecture of digital knowledge access.
Vision for a Machine-First Web
Agrawal’s vision for Parallel stems from a pivotal insight: “AI agents—not humans—will soon become the primary users of the web.” In an era where the Internet is increasingly navigated by autonomous systems, traditional infrastructure—designed for human attention and clicks—is no longer sufficient. Parallel aims to create a web environment tailored specifically for AI, focused on real-time retrieval, verification, and structured access to information.
Groundbreaking Technology: Deep Research API
At the heart of Parallel’s offering is the Deep Research API, a cutting-edge toolset engineered to provide AI agents with unparalleled research capabilities. Through multiple specialized “research engines,” the API enables agents to perform deeply accurate, multi-step web queries—and deliver results that surpass both human researchers and leading AI models like GPT-5.
One of Parallel’s engines, Ultra8x, can engage in extended, high-depth exploration. In recognized benchmarks like BrowseComp and DeepResearch Bench, it outperformed GPT-5—with Parallel achieving an accuracy rate of approximately 58%, compared to 41% for GPT-5, and just 25% for human researchers.
Strong Investor Support & Growth Momentum
Parallel Web Systems has raised $30 million from a prestigious roster of Silicon Valley investors, including Khosla Ventures, Index Ventures, and First Round Capital.
Since its founding in 2023, the company has developed a dynamic 25-person team in Palo Alto. In a short span, the platform has begun processing millions of research tasks daily, supporting use cases across coding assistance, data gathering, market intelligence, and enterprise automation.
Real-World Applications & Market Fit
Parallel’s infrastructure powers AI coding tools that fetch documentation and debug code automatically. Retailers leverage it to monitor competitor pricing and listings. Market analysts extract customer insights into organized formats. One unnamed public enterprise has even replaced traditionally human-driven workflows with Parallel’s automated system—achieving “results that exceed human-level accuracy.
Agrawal emphasizes that this is just the beginning: “Some of the fastest-growing AI companies use Parallel to bring web intelligence directly into their platforms and agents.”
Leadership & Expertise
Parag Agrawal brings a distinguished blend of technical depth and visionary leadership. A PhD graduate from Stanford University and alumnus of IIT Bombay, Agrawal spent over a decade at Twitter, rising from engineer to Chief Technology Officer, and later becoming CEO in late 2021. His tenure continued until Elon Musk’s acquisition of the company in October 2022.
Despite his abrupt exit, Agrawal remained focused. Refusing to step back, he immersed himself in AI research—reading papers, sketching ideas, and building from day one. Now, with Parallel Web Systems, he’s committed to “a new chapter in AI infrastructure,” driven by a future where AI agents autonomously navigate and act on information.
Parallel Web Systems is building foundational architecture for a new machine-aware Internet. Its APIs offer developers and enterprises a gateway to real-time, verifiable information—a critical edge over static, model-trained data. As AI agents increasingly carry out decision-making, automation, and insights generation, Parallel’s infrastructure could become indispensable.
Parag Agrawal envisions a paradigm where each user deploys dozens of AI agents on their behalf—interacting, searching, and reasoning across the web—ushering in an era of intelligent, autonomous computing.
Established in 2023 and based in Palo Alto, California, Parallel Web Systems is building the next-generation web infrastructure optimized for AI agents. Its Deep Research API enables advanced, real-time web research—outperforming human benchmarks and leading AI models. The startup has raised $30 million from top-tier investors and is powering applications across industries, from enterprise automation to AI-native products.
