Hitachi Vantara Launches Hitachi iQ Studio to Speed Enterprise AI Development
Jakarta - 07 November 2025. Hitachi Vantara introduced Hitachi iQ Studio, a platform to help teams design, test, and manage AI systems with less friction. The focus: no-code and low-code tooling so teams can build and run AI agents without leaning entirely on senior data scientists or heavy custom coding.
The company positions iQ Studio as a way to make AI more accessible while keeping enterprise performance and governance in play. For IT and development teams under pressure to ship AI use cases, the pitch is simple: cut setup time, keep data where it is, and standardize how agents are built and operated.
Why it matters
Most organizations stall moving AI from proof-of-concept to production because of skills gaps and data management hurdles. A report from Boston Consulting Group shows 74% of companies struggle to get beyond experiments due to limited experts and data complexity. That's the bottleneck Hitachi iQ Studio targets.
Key capabilities (at a glance)
- No-code/low-code agent builder: Ship internal AI agents faster and reduce dependence on full-time coders for every iteration.
- On-prem processing: Run data pipelines and models inside your environment, which helps with data residency and confidentiality requirements.
- Enterprise governance: Centralize controls for access, performance, and oversight so AI workloads meet internal policy.
- NVIDIA-accelerated stack: Built on NVIDIA AI Data Platform tech to deliver performance and scalability for training and inference.
- Data expertise from Hitachi Vantara: Leverages proven data ingestion and management practices to keep pipelines clean and reliable.
Who benefits
- Financial services, healthcare, and government teams with strict data residency and auditing requirements.
- IT leaders standardizing AI development and MLOps across multiple business units.
- Engineering teams building internal copilots, process agents, and decision support apps on top of sensitive data.
What this means for your stack
If you need AI near your data, iQ Studio's on-prem approach reduces data movement and cloud exposure. It also gives platform teams more control over performance tuning, guardrails, and cost. The NVIDIA foundation signals strong GPU support for both training and inference workloads.
Practical next steps
- Confirm data residency and compliance needs across your AI use cases (especially PII, PHI, and financial records).
- Shortlist 2-3 high-impact internal agent workflows (e.g., ticket triage, knowledge retrieval, anomaly detection) for a pilot.
- Stand up a small MLOps lane for versioning, monitoring, and rollback of agents and prompts.
- Assess hardware readiness (GPU availability, storage IOPS, network) and plan capacity for peak inference.
- Upskill your team on no/low-code agent patterns and guardrails. For structured programs, see AI courses by job.
What the companies say
"AI has grown beyond the experimental stages, but many organizations still need the right foundation to be able to scale effectively," said Jason Hardy, Chief Technology Officer for AI, Hitachi Vantara. iQ Studio is positioned to combine intuitive tooling with the governance enterprises expect.
Jacob Liberman, Director of Enterprise Product at NVIDIA, added that by combining Hitachi Vantara's data expertise with NVIDIA's accelerated computing and software, customers get the performance, scalability, and efficiency required for enterprise AI deployments.
Context and sources
Hitachi iQ Studio is built on NVIDIA AI Data Platform technology, prioritizing on-prem execution for organizations with strict confidentiality requirements. For background on NVIDIA's enterprise AI stack, see NVIDIA Enterprise Software.
The adoption gap cited comes from Boston Consulting Group, which reported 74% of companies struggle to move AI from experimentation to production. Reference: BCG.
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