Manual Recall Delays
Data trapped on tape or in siloed object buckets requires manual intervention to access.
Turn Static Archives into Active AI Resources
Unify metadata across tape and object storage to make "cold" data discoverable, accessible, and ready for advanced analytics without manual recall.
The Problem: Legacy Archives are "Dark Data" Silos
Traditional HPC archive workflows were designed for long-term retention, not modern discovery. This creates significant barriers for AI-driven research.
Invisible Datasets
If AI and large-scale analytics can't "see" the data, they can’t use it for training or reasoning
Stranded Value
Valuable historical research remains offline, effectively disconnected from the active work environment.
Modernize Your Archive for the AI Era
Hammerspace helps you modernize your long-term retention strategy without forcing a "rip-and-replace" of your existing infrastructure.
Ingest and unify metadata from archive systems (where supported) so that archived datasets are visible in the global namespace
Expose AI-relevant metadata to make archive content discoverable and policy-driven, rather than dependent on manual recall
Allow data to be brought back online on flash or high-performance disk when it is needed for AI, analytics, or new research applications
As flash capacity grows and power/space budgets tighten, Hammerspace and emerging technologies like high-density, power-efficient storage enable HPC teams to move from "deep cold" tape toward power-efficient, online flash archives.
Ready to Accelerate Your HPC Infrastructure?
See how Hammerspace can unify all your data, accelerate your high-performance computing workloads, and deliver results faster.
Book now