Hewlett Packard Enterprise (HPE) has launched its HPE Private Cloud AI solution in India, aiming to help enterprises deploy generative and agentic AI applications swiftly and at scale.
The integrated, self-service AI cloud platform enables rapid development and deployment of AI workloads, significantly reducing the time from experimentation to real-world implementation.
HPE Private Cloud AI integrates NVIDIA’s AI computing, networking, and software stack with HPE’s AI storage, compute capabilities, and the HPE GreenLake cloud.
The platform simplifies AI deployment, monitoring, and optimisation, offering enterprises a unified interface with full lifecycle management and deep observability insights across hybrid environments. It includes resource management and AIOps features and is available in flexible configurations to support many AI use cases.
Som Satsangi, SVP and managing director at HPE India, said, “As part of the NVIDIA AI Computing by HPE portfolio, this turnkey solution simplifies AI deployment and operations, speeding up innovation while ensuring reliability and security.”
The solution has also been enhanced with support for the new NVIDIA AI Data Platform, allowing organisations to transform business data into actionable intelligence. By combining NVIDIA’s accelerated computing and AI software with HPE’s infrastructure, the platform facilitates continuous data processing to fuel AI-driven actions.
Among the latest updates to HPE Private Cloud AI is a new developer system powered by NVIDIA accelerated computing. This environment includes an integrated control node, end-to-end AI software stack, and 32TB of integrated storage, offering instant AI development capabilities within the platform.
Additionally, HPE Data Fabric Software now powers seamless edge-to-cloud data access within the HPE Private Cloud AI data lakehouse. This ensures AI models are continuously fed with high-quality, optimised structured, unstructured, and streaming data across hybrid cloud environments.
To further accelerate AI deployment, the platform now includes pre-validated NVIDIA blueprints, including the Multimodal PDF Data Extraction Blueprint and Digital Twins Blueprint.
These blueprints, developed in collaboration with NVIDIA, provide fast-track implementations of complex AI workloads, improving performance and reducing time to value for enterprise customers.
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