Summary is AI-generated, newsdesk-reviewed
  • VAST Data releases Foundation Stacks to extend NVIDIA AI Blueprints for enterprise AI deployment.
  • Foundation stacks enable scalable, production-ready AI pipelines on the VAST AI Operating System.
  • VAST Foundation stacks simplify AI application deployment in the cloud and on-premises environments.

VAST Data has introduced VAST Foundation Stacks, a new open-source library designed to enhance and extend NVIDIA AI Blueprints into production-ready pipeline implementations directly on the VAST AI Operating System. 

This development aims to streamline the deployment process for enterprises using NVIDIA-powered technologies.

NVIDIA AI Blueprints

NVIDIA AI Blueprints serve as a foundational tool for developers seeking to build sophisticated AI applications and intelligent agents. These blueprints utilise NVIDIA AI Enterprise software to facilitate the rapid prototyping, customisation, and deployment of domain-specific AI workflows with minimal integration requirements.

VAST Foundation Stacks take these blueprints further by creating ready-to-use templates that facilitate seamless deployment on the VAST AI Operating System, allowing developers to concentrate on strategic business logic and rapidly deliver AI applications.

Streamlining AI deployment

Enterprises are eager to implement proven AI patterns, yet many reference models require significant integration to ensure secure and reliable operation in production environments. Often, teams must amalgamate fragmented infrastructure, orchestration layers, and data services to render AI applications deployment-ready.

VAST Foundation Stacks address this issue by transforming NVIDIA AI Blueprints into repeatable, enterprise-ready implementations that run natively on the VAST AI Operating System. This unification of data access, database services, compute orchestration, eventing, and pipeline execution allows organisations to deploy scalable AI pipelines without the complexity of building infrastructure from scratch.

Compatibility and availability

VSS ingests video and delivers insights via indexing, summaries, and Q&A on VAST AI OSThese foundation stacks can be deployed seamlessly on any system running the VAST AI OS, whether in the cloud or on-premises with VAST's new CNode-X platforms, as part of the NVIDIA AI Data Platform reference design. The initial Foundation Stacks are based on NVIDIA AI Blueprints for Video Search and Summarisation (VSS) and NVIDIA AI-Q.

The VSS-based stack allows enterprises to ingest large quantities of video and derive insights through semantic indexing, summarisation, and interactive question-and-answer functionalities, leveraging VAST AI OS's robust data and pipeline services. The AI-Q based stack offers a framework for building custom AI researchers that synthesise hours of research swiftly, providing secure and scalable reasoning pipelines.

Expert insights

John Mao, Vice President, Global Technology Alliances at VAST Data, stated, “NVIDIA AI Blueprints have given the market an important starting point for building next-generation applications, but enterprises still need a production-ready way to deploy and operate those capabilities at scale. With VAST Foundation Stacks, VAST is taking the architectural patterns behind leading NVIDIA Blueprints and giving customers a faster path from experimentation to production for scalable AI pipelines, video intelligence, and agentic AI systems.

Adel El Hallak, Vice President, Product at NVIDIA, added, “As enterprises transition to production AI at scale, preparing enterprise data for AI has become one of the biggest challenges. Turning data into AI-ready pipelines needs to be done continuously and requires full-stack acceleration across compute, networking and software. By extending NVIDIA AI Blueprints with the VAST AI Operating System, customers can prepare and serve data so intelligent agents are always working off the most recent and accurate information.

Future developments

Beyond the current VSS and AI-Q implementations, VAST plans to release additional foundation stacks in the near future, including industry-specific examples.

These will be accessible via a public GitHub repository, offering interactive demos and upcoming sandbox environments for customers and partners.

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