Data 360 — Salesforce Inc.’s unified data foundation that brings together Data Cloud, Tableau, MuleSoft and the forthcoming Informatica acquisition under one governed architecture — is emerging as the connective tissue for a new kind of enterprise intelligence, one where context, governance and data fluidity drive smarter systems and faster decision-making.

Salesforce is weaving Data 360 into its Agentforce 360 platform, creating coordinated teams of digital agents that act, learn and respond in real time. The architecture shifts from task automation to orchestrated collaboration, combining Agent Script for workflows, Agentforce Builder for vibe coding and Data 360 for real-time contextual grounding.

Salesforce’s Rahul Auradkar discusses Data 360 with theCUBE.

“We believe in this idea known as data fluidity or fluidity … the ability for the context to be available for the agent in the moment,” said Rahul Auradkar (pictured), executive vice president and general manager of unified data services at Salesforce. “We have built Data 360 from the ground up on standards … we are an open and extensible platform. That sort of an ecosystem vibrancy is needed for data fluidity that allows us to provide intelligent context in the moment.”

Auradkar spoke with theCUBE’s John Furrier and George Gilbert at Dreamforce, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed Salesforce’s vision for agentic AI and why the data component is so important. (* Disclosure below.)

Data 360 as a unifying force

Data 360 unifies structured, unstructured and metadata to deliver contextually relevant insights for business users. Rahul Auradkar illustrates this with a simple example: after buying a car, customers shouldn’t still receive car ads. By integrating unstructured data into its maturity model, Salesforce strengthens Agentforce 360’s ability to deliver smarter, more precise experiences.

“We were getting reams and reams of structured data … along with data that is sitting in Snowflake or Databricks,” he explained. “In that maturity model, we are fairly mature. That’s what Data Cloud was in the past, we were the best CDP in the market. Now, you add unstructured data. Within unstructured data, you want semantic understanding of that unstructured data, that’s what intelligent context is.”

Salesforce is also in the process of acquiring Informatica, an enterprise cloud data management platform. This move will bring greater data transparency and data understanding to Data Cloud, according to Auradkar.

“They have a governance, the catalog, they have fantastic data integration,” he said. “We can have data integration and app integration now learn from each other for our customers. You get significant value for our customers across understanding, transparency and also with the governance.”

Governance and accuracy are key with any generative or agentic AI tool. Salesforce has a Model Context Protocol head for each source of data, making it easier to get the right context. The company also continues to source feedback on its agents’ work.

“Think about it from a context that you’re providing to the agent,” he said. “Was that the right response? Was that the right action? Did the governance go right? Are we locking out people who were supposed to get access to the data? Are we locking out some actions that were supposed to be performed through governance? We keep getting that feedback.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of Dreamforce:

(* Disclosure: TheCUBE is a paid media partner for Dreamforce. Neither Salesforce, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE