Traditional enterprise data architectures are under pressure to adapt to the new reality of AI inferencing and agentic AI workloads. The problem is that enterprise data is typically distributed across incompatible silos, clouds, and even across multiple locations.

The challenge is how to deliver unified access to all of an organization’s unstructured data without costly alterations to existing infrastructure, wholesale data migrations, or investments in yet another proprietary storage repository just for AI use cases.

To unlock AI’s full potential, organizations need unified, high-performance access to all their digital assets—across multi-vendor storage silos, cloud platforms, and even multiple data centers.

This session shows how Hammerspace accelerates AI initiatives with a standards-based approach that delivers the performance AI demands inside your existing IT infrastructure. Automated data orchestration and unified file/object access bridge otherwise incompatible storage silos, locations, and cloud providers, enabling AI workloads without vendor lock-in, while controlling costs and simplifying operations.