Parag Agrawal, the former Twitter CEO who was ousted during Elon Musk’s dramatic takeover of the social media platform, has resurfaced with an ambitious new venture in artificial intelligence. His company, Parallel Web Systems Inc., has quietly raised $30 million in funding and is positioning itself at the frontier of autonomous AI agents designed to comb, interpret, and act on web data without direct human input. With a flagship product, the Deep Research API, already outperforming both human researchers and leading generative AI models on certain benchmarks, Agrawal is setting the stage for a future where AI agents—not individuals—dominate how the internet is utilized.

A Return to the Tech Stage After Twitter

For Agrawal, Parallel Web Systems represents much more than another Silicon Valley startup—it is a calculated re-entry into the industry that cast him out less than three years ago. As Twitter’s last CEO before the Musk era, Agrawal oversaw the platform’s technology backbone and later spearheaded operations until being abruptly dismissed in October 2022, when Musk finalized his $44 billion purchase of the company.

Alongside other Twitter executives, he later moved to sue Musk, claiming they were deprived of roughly $128 million in severance pay after their contracts were terminated. The case remains in litigation, with no final resolution to date.

Despite that corporate fallout, Agrawal never lost faith in his long-term expertise: artificial intelligence. Having led Twitter’s machine learning development during his tenure as CTO under Jack Dorsey, he knew his next act wouldn’t be about salvaging legacy companies, but about shaping the future of AI.

Founding Parallel Web Systems

After his departure from Twitter, Agrawal deliberately resisted offers to step in as a turnaround executive at struggling firms—positions he described as requests to “clean up messes.” Instead, he immersed himself in reading current AI research, experimenting with fresh codebases, and identifying where AI could evolve beyond chat-style interfaces.

That exploratory phase crystallized into Parallel Web Systems Inc., a company devoted to one clear mission: empowering AI agents to autonomously collect, process, and analyze information across the internet at levels unattainable for humans.

At the core of this vision stands the company’s first commercial product, the Deep Research API. According to Agrawal, the tool already facilitates millions of research tasks each day and is operational inside at least one publicly traded corporation, where it has begun automating human research workflows. Additionally, AI-powered coding agents have deployed Parallel tools to efficiently locate debugging resources and technical documentation.

Most notably, Agrawal asserts that Deep Research API has surpassed both human researchers and OpenAI’s GPT‑5 on select benchmarks, signaling that the company’s technology is not merely derivative of existing models but represents a distinct progression in practical AI utility.

$30 Million in Early Funding and a Lean Team

Investors have followed Agrawal into this new frontier with conviction. Parallel has already raised $30 million in funding while maintaining a lean staff count of approximately 25 employees, according to reports. Such an early-stage capital infusion suggests that backers recognize the strategic significance of his bet on autonomous AI systems at a time of intense competition in the sector.

In the current climate, where venture markets are more selective, raising this level of funding speaks not only to Agrawal’s reputation but also to the market expectation that AI agents will soon account for a dominant share of online activity.

The Coming Age of AI Agents

Agrawal’s core thesis is bold: AI agents will outnumber humans online sooner than many anticipate.

In a recent interview, he predicted that as early as next year, individuals may deploy dozens of AI agents per person, each independently navigating the internet on its owner’s behalf. Rather than people entering queries or scrolling feeds, autonomous agents would conduct research, negotiate digital services, solve technical issues, and even aggregate information from across the web in real time.

This vision puts Parallel in competition not only with OpenAI and Anthropic but also with a handful of emerging firms focused on agent-based systems. What differentiates Parallel, however, is Agrawal’s explicit insistence that the internet of tomorrow will be designed less for human consumption and more for machine-to-machine interaction, with AI entities acting as proxies for human decision-making.

If realized, the implications would be sweeping:

Search and information retrieval would shift from individual use to continual background processes done by fleets of agents.

Corporate research teams may see roles redefined as automated workflows handle much of their discovery and data synthesis.

Consumer behavior on the web would evolve, with agents brokering content, purchases, and digital services on behalf of users.

Strategic Takeaways for AI Startups

Investors evaluating the AI sector should recognize Parallel as illustrative of a larger industry trend: the migration of AI from conversation-driven models to autonomous, task-completing agents.

The move from reactive AI (chat, Q&A) to proactive AI (autonomous research and execution) represents a higher-margin proposition, as enterprises will pay more for tools that reduce human labor costs.

Agrawal’s personal credibility—having navigated the upper echelons of Twitter and built its machine learning infrastructure—makes Parallel more than a speculative venture.

The market for AI agents is still early-stage, meaning the potential upside rivals the early era of mobile apps or cloud infrastructure.

For professional investors, the question is not whether these agents will emerge, but who will define the standards and own the platform layer. Parallel, with its narrowed focus and specialized API, has positioned itself as a serious contender in that race.