3476 How Denodo's DeepQuery Brings Reasoning to Enterprise AI

Nov 5, 2025

In this conversation, Alberto Pan, Chief Technology Officer at Denodo, delves into how Deep Query is revolutionizing enterprise AI with its reasoning capabilities. He explains how this AI functions as a research agent, unifying live data and offering real-time insights. Alberto highlights the importance of explainability, showcasing how Deep Query allows users to trace insights back to their origins. He also discusses the Model Context Protocol and its role in enhancing AI interoperability. Expect a future where analysts guide AI-driven research seamlessly.

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INSIGHT

AI That Plans And Adapts

DeepQuery acts as an AI reasoning agent that plans, queries live systems, analyzes results, and adapts its steps.
It generates full research reports with data, dashboards, and recommendations automatically.

INSIGHT

Analysts Become Research Guides

DeepQuery reframes BI roles: analysts become guides rather than manual report builders.
The assistant performs data collection and analysis while humans interpret and guide.

ADVICE

Expose Data Through A Semantic Layer

Keep data where it lives and expose it via a logical semantic layer to avoid new silos.
Use business semantics to give AI context and reduce ambiguity and hallucinations.

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What if business intelligence didn't stop at answering what happened, but could finally explain why? In this episode of Tech Talks Daily, I sit back down with Alberto Pan, Chief Technology Officer at Denodo, to unpack how DeepQuery is redefining enterprise AI through reasoning, transparency, and context.

We explore how DeepQuery functions as an AI reasoning agent capable of performing open-ended research across live, governed enterprise data. Instead of relying on pre-built dashboards or static reports, it builds and executes multi-step analyses through Denodo's logical data layer, unifying fragmented data sources in real time. Alberto explains how this semantic layer provides the business meaning and governance that traditional GenAI tools lack, transforming AI from a surface-level Q&A system into a trusted analytical partner.

Our conversation also digs into the bigger picture of explainable AI. DeepQuery reports include a full appendix of executed queries, allowing users to trace every insight back to its source. Alberto breaks down why this level of auditability matters for enterprise trust and how Denodo's support for the Model Context Protocol (MCP) opens the door to more interoperable, agentic AI systems.

As we discuss how DeepQuery compares with RAG models and data lakehouses, Alberto offers a glimpse into the future of business intelligence—one where analysts become guides for AI-driven research assistants, and decision-makers gain faster, deeper, and more transparent insights than ever before.

So what does the rise of reasoning agents like DeepQuery mean for the next generation of enterprise AI? And how close are we to a world where AI truly understands the why behind the data? Tune in and share your thoughts after listening.

Useful Links

Connect with Alberto Pan on LinkedIn

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