An analytics platform, no matter how intelligent, is only valuable if it integrates seamlessly into the tools and workflows where decisions are actually made. A common reason for the "dashboard plateau"—where BI adoption stagnates—is that insights are locked away in a separate application, requiring users to context-switch away from their primary work. A key theme from our webinar Q&A was about embedding and integration, which speaks to a core design principle of Cube D3: it is built to be an open, interoperable, and composable platform.

D3 is not a monolithic application. It is an agentic engine designed to deliver trusted analytics wherever you need it. We provide multiple pathways to bring this power into your existing ecosystem, catering to different personas and use cases.

[Visual 1: The Hub-and-Spoke Integration Diagram]

For the Analyst: AI-Native Workbooks

The native interface within Cube Cloud serves as the "cockpit" for data analysts. Here, they can have long-form conversations with the AI Data Analyst and create complex reports in Workbooks. Unlike traditional BI, these workbooks are AI-native. The AI can generate the initial report, and the human can then refine it by clicking, dragging, and adjusting filters. It's not "automation vs. control"—it's both, in a single collaborative space.

For the Business User: Augmenting Existing BI Tools

Most organizations aren't ditching their BI tools, nor should they. D3 is designed to augment them. Because D3 and tools like Power BI can both connect to the same universal semantic layer, they work in harmony. When an analyst uses a D3 agent to create and certify a new metric, that metric can instantly become available in a Power BI dashboard. This ensures that your AI-driven insights and your traditional reports always share the same source of truth, eliminating data silos.

For the Developer: Custom and Embedded Experiences

For organizations that want to build fully custom data experiences, D3 offers powerful APIs:

  • Streaming API & iFrames: For embedding conversational analytics into internal portals or customer-facing products, you can use our streaming API to build a custom front-end or simply embed the D3 chat interface with an iFrame.
  • A2A and MCP for Multi-Agent Systems: This is the most advanced pattern. As enterprises build their own specialized AI agents, those agents can call upon a Cube D3 agent as a specialized "tool" to retrieve governed data. This enables a true "digital data team" architecture, where each agent focuses on what it does best, and D3 serves as the universal, trusted data specialist for the entire system.

Whether you are a business user in Power BI, an analyst in a D3 Workbook, or an AI architect designing a multi-agent enterprise, D3 is designed to deliver trusted, agentic analytics wherever you work.

To get on the waitlist for Cube D3, please visit our website.