Parallel Web Systems, the AI startup founded by former Twitter CEO Parag Agrawal, has raised $100 million in Series B funding, valuing the company at $2 billion. The round was led by Sequoia Capital, with participation from existing investors including Kleiner Perkins, Index Ventures, and Khosla Ventures.

The startup focuses on developing AI agents capable of autonomous web search, targeting tasks that typically require human researchers:

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Typical use cases for Parallel Systems’ AI agents:

tasks = [ “investment research”, “risk underwriting analysis”, “insurance claims processing”, “government contract review”, “deep research tasks” ] “n According to Agrawal, these AI agents can accomplish web-based research tasks at greater scale and speed than human researchers. The recent funding acceleration reflects growing investor interest in “long-horizon” or “long-running” AI agents—systems that maintain context over extended periods while processing user requests autonomously.

Sequoia partner Andrew Reed, who joins Parallel’s board as part of the deal, noted the startup’s traction stems from its development of these persistent AI agents that operate continuously in the background.

The funding positions Parallel Systems to compete in the emerging market of autonomous AI research tools, a sector seeing significant investment as enterprises seek to automate information-intensive workflows.