Dell Technologies, the world’s leading provider of AI infrastructure, has announced significant advancements to its Dell AI Data Platform, designed to help enterprises unlock the value of distributed and siloed data to accelerate AI initiatives. The platform, a core component of the Dell AI Factory, is built to simplify data complexity, unify data pipelines, and deliver AI-ready data at scale. As AI adoption grows across industries, organizations face increasing challenges in managing fragmented data across on-premises, cloud, and edge environments. The Dell AI Data Platform addresses this by decoupling data storage from processing, eliminating performance bottlenecks and enabling greater flexibility for AI workloads such as model training, fine-tuning, retrieval-augmented generation (RAG), and inferencing. The platform is built on four key components and is integrated with the NVIDIA AI Data Platform reference design, providing a powerful, open, and modular foundation for enterprise AI. Dell PowerScale and Dell ObjectScale serve as the platform’s storage engines, delivering high performance, security, and multi-protocol access essential for AI data workloads. These systems are optimized for large-scale data operations, with performance benchmarks showing superior object read throughput and low latency, especially in configurations using ObjectScale XF960 and RDMA networking. Dell is also expanding its data engines—specialized tools that organize, query, and activate AI data. In collaboration with industry leaders like NVIDIA, Elastic, and Starburst, the platform now includes new capabilities that enhance real-time AI processing. The Data Analytics Engine, developed with Starburst, enables seamless querying across diverse data sources including spreadsheets, databases, cloud data warehouses, and lakehouses. The new Data Analytics Engine Agentic Layer uses large language models (LLMs) to automatically generate documentation, extract insights, and embed AI directly into SQL workflows. It also unifies access to vector stores, supporting RAG and advanced search across formats like Iceberg, Dell’s Data Search Engine, PostgreSQL with PGVector, and more. Enterprise-grade AI model monitoring and governance tools help teams track, audit, and manage AI usage securely. Additionally, the new MCP Server for the Data Analytics Engine supports multi-agent systems and the development of complex AI applications. Industry leaders are highlighting the platform’s transformative potential. Arthur Lewis, president of Dell’s Infrastructure Solutions Group, said the platform is purpose-built to help organizations move from AI pilots to production at scale, with real-world applications in healthcare, manufacturing, and beyond. NVIDIA’s Justin Boitano emphasized that AI is finally enabling enterprises to treat data as a strategic asset, and the Dell AI Data Platform, powered by NVIDIA AI, delivers intelligent storage capable of understanding data context. Elastic’s Ajay Nair noted that integrating the Elasticsearch context engineering platform into the Dell AI Data Platform enhances search, discovery, and generative AI pipelines, turning unstructured data into actionable intelligence. Starburst’s Justin Borgman said the collaboration allows organizations to access data from any source, accelerating the path to real-world AI outcomes. Maya HTT’s Remi Duquette highlighted how the integration of Dell PowerScale with NVIDIA AI infrastructure is driving innovation in industrial AI, from satellite production to real-time vessel telemetry, improving efficiency, safety, and sustainability. The Dell AI Data Platform is now available to customers, offering a scalable, secure, and open foundation for enterprise AI success.