Union.ai closed a $38.1 million Series A round led by NEA, with participation from Nava Ventures and new investor Mozilla Ventures, targeting the pilot-to-production infrastructure gap that has become a critical bottleneck for enterprise AI deployment.

This funding addresses a fundamental architectural challenge: legacy software infrastructure designed for deterministic processes struggles with AI workflows that adapt and make runtime decisions. Union’s orchestration platform, built around the open-source Flyte framework with 80+ million downloads, enables dynamic AI workflows that can recover from failures and make decisions at runtime—exactly what autonomous agents require for production deployment.

Nimble raised $47 million in Series B funding led by Norwest to solve a critical bottleneck in enterprise AI agent deployment: reliable access to real-time, structured web data that agents can actually trust for business decisions.

The New York-based company addresses what CEO Uri Knorovich calls the core enterprise AI failure mode: “Most production AI fails aren’t because the models are not good enough — it’s because of a data failure.” While AI agents excel at web search and analysis, they typically return unstructured text prone to hallucinations and unreliable sourcing, creating an insurmountable trust gap for enterprise deployment.

Potpie AI raised $2.2 million to build structured context layers that allow AI agents to operate effectively across enterprise-scale codebases exceeding 40 million lines of code.

The infrastructure gap isn’t computational power—it’s organizational memory. While large language models excel at code generation, they struggle to maintain context across complex, interconnected systems where critical knowledge lives in senior engineers’ heads and context spans dozens of tools and millions of lines of legacy code.