Building at the speed of agents: from training pipelines to data infrastructure

Agentic AI pushes infrastructure to its limits. To train models that see, understand, and act, teams need high-throughput storage, clean pipelines, and architectures that scale with evolving datasets.

H Company and VAST Data unpack how they approach these challenges: designing agent-oriented models, managing fast-moving training workflows, and building the data backbone that keeps iteration cycles short.

A focused look at the engineering trade-offs behind the next generation of AI systems.