Hitachi Vantara adds AI analytics tools to VSP One

Hitachi Vantara has added features to its VSP One data platform and Hitachi iQ portfolio, focused on object storage, data lakehouse analytics and governed access to enterprise data for AI use.

The update centres on enhancements to VSP One Object, which now starts with a four-node configuration designed to lower the entry point for organisations building storage for AI and analytics workloads. The release targets companies looking to move AI projects beyond pilot stages into broader operational use.

Industry data cited by Hitachi Vantara points to a gap between AI adoption and deployment at scale. McKinsey's 2026 State of AI survey found that nearly nine in 10 respondents said their organisations regularly use AI in at least one business function, while 44% said AI was scaling across the enterprise. IDC research, also cited by the company, found that 89% of organisations reported some level of data-quality problem.

The storage changes include simpler deployment and performance improvements for small-object workloads. According to Hitachi Vantara, VSP One Object can provide up to 5.5 times faster access to data for AI, analytics and S3 workloads, while expanded multisite replication and regional features are intended to improve resilience and availability.

Analytics shift

A key part of the release is the addition of analytics functions directly on VSP One Object. The platform can query supported open-format data, including Iceberg, Parquet, JSON and CSV, where it resides rather than requiring it to be moved into a separate analytics environment.

Hitachi Vantara said this approach supports up to five times faster analytical query performance with 80% fewer CPUs. Reducing data movement could also help organisations limit duplicate datasets, data pipelines and the infrastructure needed to manage them.

That focus reflects a broader industry effort to cut the cost and complexity of preparing enterprise data for AI systems. Many organisations have struggled to connect large volumes of operational and unstructured data to AI models without creating new silos or governance issues.

AI software layer

VSP One underpins Hitachi iQ, the company's AI infrastructure and software offering. In the latest release, Hitachi iQ Studio expands access to both structured and unstructured data for retrieval-augmented generation, or RAG, including filesystem and NFS knowledge sources.

The update is intended to let organisations use more enterprise data in AI applications and agents without first moving or restructuring all of it. Hitachi iQ Studio also adds a Model Gateway for governed access to local and external models, governed Model Context Protocol connectivity and ServiceNow support.

Other additions include role-based access controls, observability and lifecycle management for AI applications and agents. Together, these features are intended to strengthen oversight of model use, data access and operational management in enterprise AI environments.

Octavian Tanase, Chief Product Officer at Hitachi Vantara, said the company sees data management and AI deployment as increasingly linked.

"AI strategy is now inseparable from data strategy. As AI becomes part of more business-critical workloads, the infrastructure underneath it has to make it easier to put enterprise data to work," said Octavian Tanase, Chief Product Officer at Hitachi Vantara. "With VSP One, we're giving customers a practical way to build the data foundation for AI, bring analytics closer to their data and scale with confidence as demand grows. That creates a stronger path from experimentation to production without sacrificing the resilience and control enterprises depend on."

Broader context

The release shows how storage suppliers are repositioning infrastructure around AI requirements rather than traditional capacity and performance measures alone. Vendors are increasingly trying to combine data storage, analytics and governance tools into a more unified stack for enterprises concerned about data locality, oversight and cost.

Hitachi Vantara is also combining its infrastructure and software with wider industry expertise from Hitachi to address operational use cases. It linked the approach to work under the Hitachi AI Factory banner, which focuses on moving AI systems from experimentation into production environments tied to business operations.

For customers, the significance of the release may rest less on any single feature than on whether the platform can reduce the friction involved in preparing, governing and analysing data for AI workloads. The additions to object storage, native analytics and governed model access suggest Hitachi Vantara is trying to address that bottleneck directly, at the point where enterprise data is stored and managed.

VSP One Object now combines a smaller starting configuration, direct querying of open-format data and expanded replication features with software designed to control how AI applications and agents access enterprise information.