Benchmark has led an $85 million Series B round in Exa Labs at a $700 million valuation, betting that the next wave of AI infrastructure will be purpose-built for agents, not retrofitted from human-centered systems.

This timing reflects a fundamental shift: as AI agents become the primary interface between enterprises and web-scale data, the search infrastructure powering these interactions has become a critical bottleneck. Exa’s neural search architecture delivers sub-450ms latency with zero data retention, addressing the dual enterprise demands of speed and privacy that traditional search engines can’t meet at agent scale.

Refold AI emerged from stealth with $6.5M in seed funding to tackle enterprise system integration through AI agents, addressing what the company calls the “integration tax” that costs enterprises billions annually in consultant fees and project delays.

The Bengaluru and San Mateo-based startup’s platform deploys autonomous agents to write, test, and maintain complex enterprise integrations—work traditionally requiring armies of billable-hours contractors from firms like Accenture and Infosys.

The Enterprise Integration Bottleneck

Enterprise system integration represents a massive operational bottleneck where companies spend months and six-figure budgets connecting disparate software systems. The traditional approach relies heavily on human consultants who manually map data flows, write custom code, and maintain integrations as systems evolve.