Create one governed copy of enterprise data that powers analytics, AI applications, and intelligent agents. Eliminate fragmented data architectures with an open lakehouse built to scale from traditional analytics to enterprise AI.

Preserve what AI learns across every interaction, making knowledge discoverable, reusable, and available to every agent. Deliver only the most relevant context to AI models, improving response quality while reducing latency and token costs, all while keeping your knowledge secure, governed, and under your control.

Never rebuild context twice. Persist and share inference context across GPUs with sub-10ms context memory, eliminating recompute to deliver faster responses, higher GPU utilization, and lower inference costs.

Purpose-built for AI training at scale. AIStor re-engineers the data path for modern GPU infrastructure to deliver up to 23.5 TiB/s of throughput, keeping GPU clusters continuously supplied with data, checkpointing large scale foundation-parameter models in seconds, and eliminating the bottlenecks that slow AI training.