Qumulo Bridges On-Premises and Cloud Data for AI Workloads
Qumulo has repackaged its data management products into the Cloud AI Accelerator, designed to reduce infrastructure costs and improve GPU efficiency for organizations running AI workloads across multiple environments.
The company initially released the accelerator in November 2025. It combines several existing Qumulo products to unify on-premises and cloud-based data in a single system.
Partnership with Cisco Expands Reach
Qumulo announced a partnership with Cisco to integrate its technology with Cisco's Unified Computing System (UCS). The collaboration, called the Bridge-to-Cloud solution, targets organizations that run file workloads both on-premises and in the cloud.
The timing aligns with Cisco Live, Cisco's annual conference where the company typically showcases new infrastructure products.
What This Solves
The accelerator addresses three specific problems for data teams:
- Eliminates the need for expensive all-flash storage hardware
- Centralizes data management across on-premises and cloud environments
- Increases GPU utilization by improving data access patterns
For managers overseeing AI infrastructure budgets, the cost reduction alone may justify evaluation. GPU hardware remains one of the largest expenses in AI deployments, and anything that improves utilization directly impacts return on investment.
The Broader Context
Data management has become a bottleneck in AI deployments. Organizations often struggle to move training data efficiently between storage systems, which can leave expensive GPUs idle while waiting for data to arrive.
Qumulo's approach addresses this by treating hybrid cloud environments as a single data pool rather than separate systems requiring manual coordination.
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