Former Twitter CEO Parag Agrawal’s Parallel Web Systems has raised $100 million to solve a fundamental mismatch: the internet was built for humans, but AI agents are becoming its primary users.

This infrastructure bottleneck matters because enterprise AI systems require real-time web access to function effectively, yet current search APIs waste computational resources delivering human-readable results that agents can’t efficiently process.

The Human Web Bottleneck

The modern web infrastructure assumes human users who click links, scan visual layouts, and parse information contextually. AI agents operate differently—they need structured, tokenized data that feeds directly into model context windows without the overhead of HTML rendering, visual formatting, or click-through workflows.