Elyos AI just closed a $13 million Series A round led by Blackbird Ventures to tackle one of the most significant and overlooked bottlenecks in AI deployment: the operational infrastructure of traditional industries.

The timing is critical. As the AI infrastructure boom creates unprecedented demand for skilled trades workers—from electricians building data centers to HVAC technicians maintaining them—the very businesses supplying this labor are being choked by analog operational friction, preventing them from scaling to meet demand.

InstaLILY just raised $25 million in Series A funding led by Insight Partners, but the real story isn’t the capital—it’s the 70% reduction in manual review times their vertical AI agents are delivering across distribution-heavy industries.

This signals a crucial shift in enterprise AI deployment. While horizontal platforms chase general-purpose capabilities, InstaLILY’s success reveals that the path to production AI lies through industry-specific execution, not generic assistance.

The Distribution Industry Bottleneck

Most enterprise AI deployments stall at the same point: complex, multi-step workflows that require domain expertise, legacy system integration, and actual decision-making authority. Distribution-heavy industries—from industrial parts suppliers to insurance providers—represent the hardest test case for AI automation. These sectors depend on massive catalogs, specialized knowledge, fragmented toolchains, and exception handling that defeats traditional RPA approaches.