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Teradata Enterprise Vector Store Joins NVIDIA Enterprise AI Factory Validated Design

Learn how Teradata and NVIDIA are enabling enterprises to move toward scalable, agentic AI systems.

Meeta Vouk
Meeta Vouk
June 11, 2025 3 min read

Sovereign AI is quickly becoming a national imperative for countries seeking to secure their digital futures and drive innovation. At NVIDIA GTC Paris, customers and partners alike learn about the importance of sovereign AI for safeguarding national interests; ensuring data privacy and legal compliance; driving economic and technological progress; and building regionally sensitive AI solutions that understand and preserve regional cultural identities.

Sovereign AI encapsulates a nation’s ability to produce artificial intelligence using its own infrastructure, data, workforce, and business networks. This approach ensures that countries retain ownership over their data, digital intelligence, and the AI models they develop.

Teradata Enterprise Vector Store joins NVIDIA Enterprise AI Factory validated design

As enterprises accelerate their AI strategies, NVIDIA is bringing together a powerful ecosystem of technologies to support scalable, secure, and sovereign AI development. A key part of that ecosystem is the NVIDIA Enterprise AI Factory validated design—a validated design optimized for building and deploying AI agents across industries like finance, healthcare, and government.

We’re excited to share that Teradata’s Enterprise Vector Store is included as part of this validated design. 

This integration gives enterprises a high-performance, in-database vector solution that brings structured and unstructured data together and works seamlessly with NVIDIA accelerated computing and AI software—enabling organizations to build retrieval-augmented generation (RAG) and agentic AI applications that are grounded in their own data, deployed on their own terms, and optimized for real-time insight.

A foundation for sovereign AI

The Enterprise AI Factory validated design is built for organizations that need to develop AI agents using regional or enterprise-specific data—often in highly regulated environments. It includes:

By integrating with this stack, Teradata’s Enterprise Vector Store helps enterprises manage and retrieve insights from massive volumes of unstructured data—text, PDFs, images, video, and more—while maintaining full control over data privacy, governance, and infrastructure. These capabilities make the economics of generative AI more attractive to customers.

Why Teradata’s Enterprise Vector Store?

Unlike traditional vector stores that force trade-offs between speed and scale, Teradata’s solution delivers both. It processes billions of vectors with millisecond response times, and it’s built to integrate directly into existing enterprise systems—whether deployed in the cloud, on premises, or in hybrid environments.

Key capabilities include:

  • Multi-modal vector support for diverse data types
  • End-to-end vector lifecycle management, from embedding to intelligent search
  • Support for LangChain, RAG, and Trusted AI frameworks
  • Planned temporal vector embedding for explainability and trust

And, with NVIDIA NeMo Retriever now integrated, developers can fine-tune microservices and models to build scalable, real-time RAG applications that connect to proprietary data wherever it resides.

Building toward agentic AI

Together, Teradata and NVIDIA are enabling enterprises to move beyond isolated AI experiments and toward scalable, agentic AI systems that are deeply integrated with business operations. Whether it’s cybersecurity, regulatory compliance, or augmented customer service, this joint ecosystem provides the tools and infrastructure to turn unstructured data into actionable intelligence—securely, efficiently, and at scale.

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About Meeta Vouk

Meeta Vouk is vice president, product management, analytics and AI/ML at Teradata. She is a seasoned product leader with extensive experience in AI, advanced computing, and application integration. Vouk was previously at IBM, where she led several successful product portfolios and drove AI strategy and execution for IBM mainframes. She holds a PhD in ASIC design and has been an adjunct professor at North Carolina State University for 17 years.

View all posts by Meeta Vouk
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