Hitachi Vantara focuses on AI with partnerships

Hitachi is working to help its Hitachi Vantara subsidiary respond faster to AI adoption and development, according to its CTO. In late 2023, Hitachi Vantara was reorganized, and Sheila Rohra became CEO.

It created a unified storage product data plane, a unified product control plane, and an integrated data-to-agent AI capability. VSP One, the unified data plane, launched in April last year, and all-QLC flash and object storage products were added late in 2024. The unified control plane VSP 360 was announced a week ago. The AI capability is branded Hitachi iQ, and will be applied across the Hitachi group’s product portfolio. Jason Hardy, Hitachi Vantara’s CTO for AI and a VP, presented Hitachi iQ at an event.

The data plane includes block, file and object protocols and mainframe storage. A new VSP Object product is coming later this year, S3-based, developed in-house by Hitachi Vantara, and will replace the existing HCP-based object storage product, which will be retired. Hitachi Vantara is unifying VSP One file and object with its own in-house development, which started a year ago. There has been no demand to unify block with file and object.

The data plane is hybrid, covering on-premises and using AWS, Azure and GCP. VSP 360 is an update of the existing Ops Center, and will play a key role in how AI facilities are set up to use VSP One and how they are instantiated. VSP 360 gives observability into VSP One’s carbon footprint, and the next generation will enable user action.

A user could choose a more sustainable option if VSP 360 reveals that the footprint is getting high and alternatives are available. This will be driven by agentic AI capabilities. The VSP One integrated and hybrid storage offerings, managed, observed and provisioned through VSP 360, form the underlying data layer used by Hitachi iQ.

Hitachi Vantara has been working with Nvidia on projects, including engagements with Hitachi group businesses such as Rail where an HMAX digital asset management system, using Nvidia GPUs in its IGX industrial AI platform, has enabled a lowering of maintenance costs and a reduction in train delays. Hitachi Vantara also has an NvidiaBasePOD certification.

Hardy told B&F that Hitachi iQ is built on 3 pillars: Foundation, Enrichment and Innovation. The Foundation has requirements aligned with Nvidia and Cisco and is an end-to-end offering equivalent to an AI Factory for rapid deployment. Enrichment refers to additional functionality, advisory services and varied consumption models. A Hammerspace partnership extends the data management capabilities, a WEKA deal provides high-performance parallel file capabilities, and the data lake side is helped with a Zetaris collaboration. Innovation refers to vertical market initiatives, such as Hitachi iQ AI Solutions use case documentation, and projects with partners and Nvidia customers.

A Hitachi iQ Studio offering is presented as a complete AI solution stack spanning infrastructure to applications and running across on-prem, cloud, and edge locations. It comprises an iQ Studio Agent and Studio Agent runtime with links to Nvidia’s NIM and NeMO Retriever microservices extracting and embedding data from VSP One object and file, and storing the vectors in a Milvus vector database.

There is a Time Machine feature in iQ which enables the set of vectors used by a running AI training or inference job to be modified, during the job’s execution and without topping the job. Incoming data is detected by iQ and embedding models run to vectorize it, with the vectors stored in a Milvus database. The embedding is done in such a way as to reserve, in metadata vectors, the structure of incoming data.

If a document file arrives, this has content and file-level metadata; author, size, date and time created, name, etc. The content is vectorized as is the metadata so that the vectorized document entity status is stored in the Milvus database as well. If a set of vectors which includes the content ones from the document becomes invalid during the AI inference or training run, because the document breaks a privacy rule, the document content vectors can be identified and removed from the run’s vector set in a roll back type procedure. That’s why this feature is called a Time Machine.

The Hitachi iQ product set is moving the company into AI storage and agentic work, hooking up with Nvidia, joining players such as Cisco, Dell, HPE, Lenovo, NetApp and Pure Storage. It’s done this by a combo of partnering and in-house development, leaving behind its previous acquisition mindset. Hitachi V is in a hurry and AI is its perceived route to growth.