Dell AI Data Platform adds knowledge graph for agents

Dell is pitching its platform at a specific gap: enterprise data that was never organized with an AI reader in mind. Much of it predates agents entirely, and Dell argues agents end up burning tokens on every query to piece together answers that should already exist. Its answer is three linked components that run inside the customer's own data center because they hold sensitive information.

The processing side is a separate bet. Dell's September tests on a PowerEdge R770 server found Apache Spark jobs ran 3.9 times faster on average than on CPUs alone, with a 20.4-times best result on a batch data mining job, and Dell noted the tests used default settings with no tuning. Arthur Lewis, president of Dell's Infrastructure Solutions Group, framed the point bluntly: an agent that can find a customer record but has no idea what it means or whether it can be trusted "isn't intelligent." He said it is "just fast."

The rollout is staggered rather than simultaneous. PowerScale's multitenancy and security updates arrive in November, the accelerated Data Processing Engine follows in December, and the semantic layer, knowledge graph and knowledge agents land in the first half of 2027. That gap means the value Dell describes depends on customers trusting its definitions enough to standardize on them, which is likely to be a longer organizational task than a software upgrade.