Dell Technologies has announced the expansion of its Dell AI Data Platform, introducing new features designed to improve the way AI agents use and interpret enterprise data.
The company says the updates will provide applications and agents with trusted, up-to-date context from a business’s own information, aiming to deliver more accurate responses, lower operational costs, and reduce the time needed to reach production.
Go deeper with GlobalData
Access deeper industry intelligence
Experience unmatched clarity with a single platform that combines unique data, AI, and human expertise.
According to Dell, making enterprise data usable for AI systems remains a barrier for organisations, as most business information is stored in separate files, databases, and cloud services across various locations.
These data sources often lack the structure required for machine reading, which can lead to increased computational demands and less reliable outputs when AI agents process queries.
The updated Dell AI Data Platform incorporates several new components intended to address these challenges.
The Unified Semantic Layer standardises the meaning of business terms across structured and unstructured data, supported by rules, definitions, and a searchable glossary.
Dell has enabled customers to import established ontologies and classification taxonomies and has added support for Nvidia Auto-Ontology, which creates knowledge graphs from enterprise data.
Alongside this, Dell has introduced the Enterprise Knowledge Graph, which maps relationships between different data types using metadata, lineage, and query history.
This helps AI agents and applications retrieve context relevant to a specific request, such as identifying links between sensor readings, maintenance records, supplier batches, and purchase orders.
The platform’s new Knowledge Agents are set up by customers and operate as focused advisers on specific topics, providing guidance based on the section of the Enterprise Knowledge Graph to which they are assigned.
Customers retain control over data access, quality standards, and spending limits.
Nvidia Nemotron Retriever models are used to support reasoning capabilities.
Dell says these features keep sensitive information within the customer’s own infrastructure and maintain compatibility with different models, data sources, and storage systems.
Additional updates include accelerated data processing with Nvidia cuDF. Tests show performance up to four times faster than CPUs and up to 20 times faster for batch processing workloads when using Nvidia RTX PRO 4500 Blackwell Server Edition GPUs.
Dell’s PowerScale now allows up to 500 tenants in a single cluster, with improvements in data encryption and access control.
The company is also expanding its implementation services, aiming to help organisations transition from deploying the AI Data Platform to achieving production outcomes.
Dell Technologies infrastructure solutions group president Arthur Lewis said: “Data without context is just noise. Most enterprises have spent years making their data accessible.
“That’s not the same as making it usable.
“An agent that can find a customer record but doesn’t know what it means, how it connects to everything else, or whether it can be trusted isn’t intelligent. It’s just fast. The companies that solve it won’t just deploy AI faster or run more agents. They’ll get more out of the data they already have.”
In May 2026, Dell introduced new updates to its AI Factory offering with Nvidia, designed to assist enterprises in moving from AI planning to real-world implementation.
