Ex-Twitter CEO Parag Agrawal Launches AI Startup ‘Parallel’ to Build a Web for Machines

Three years after his sudden exit from Twitter following Elon Musk’s takeover, Parag Agrawal is back at the forefront of tech innovation with a bold new venture—Parallel Web Systems. This AI-focused startup aims to revolutionize how artificial intelligence systems interact with the internet, introducing tools that empower AI agents to perform complex web tasks with unprecedented speed and precision.

What is Parallel? A New Vision for the AI-Driven Web

Parallel Web Systems isn’t just another AI company—it’s building what Agrawal calls the “web’s second user”: machines. The startup’s mission is to create web infrastructure specifically for AI, allowing machines to not only browse the web but consume, process, and act on information more effectively than humans ever could.

Agrawal explained that AI agents—autonomous programs that can perform actions—will become the primary users of the web in the future, executing research, analysis, and automation at a scale far beyond human capability.

Key Technologies and Products

At the heart of Parallel’s offerings are its deep research APIs and low-level search tools, all designed for AI-native web interaction. These tools allow developers to build systems where,

• AI agents complete hours of human research in minutes
• Custom infrastructure powers each layer, from web crawling and indexing to search ranking
• Applications span multiple industries such as finance, healthcare, insurance, and sales

Examples of use cases already in action include,

• AI sales agents researching potential leads
• Coding agents extracting and synthesizing documentation
• Financial tools analyzing SEC filings for investment opportunities
• Insurance systems automating claims using real-time web verification

Benchmark-Breaking Performance

Parallel’s AI tools aren’t just fast—they’re exceptionally accurate, outperforming even leading models like GPT-5,

BrowseComp benchmark (multi-hop web navigation & reasoning)

• Parallel: 58% accuracy
• GPT-5: 41%
• Human (2-hour limit): 25%

DeepResearch Bench (depth & quality of long-form research)

• Parallel win rate: 82%
• GPT-5 win rate: 66%

These scores reflect Parallel’s commitment to machine-optimized infrastructure, focusing not on how humans browse, but on how machines consume, verify, and generate information at scale.

The Team and Vision Ahead

Parag Agrawal, a graduate of IIT Bombay and PhD holder from Stanford University, brings nearly a decade of experience from Twitter to his first major startup venture. Backed by $30 million in venture capital from top Silicon Valley firms like Khosla Ventures, Index Ventures, and First Round Capital, Parallel is also supported by a team of former engineers from Twitter, Google, Stripe, Waymo, and Airbnb.

Looking ahead, Parallel plans to,

• Develop long-horizon AI agents capable of completing multi-day research in hours
• Build event-driven systems that monitor the web continuously
• Introduce SQL-like query tools to interact with online data in real time

These tools will empower organizations to build fully autonomous AI workflows, where agents can perform, analyze, and iterate tasks across domains with minimal human input.