The Denodo Platform establishes a shared semantic and logical layer that standardizes business definitions, relationships, and reusable integration logic across Databricks and distributed enterprise systems. Business users, applications, and AI agents can consume trusted context without repeatedly reconstructing joins, definitions, or data relationships—reducing friction, inconsistency, and unnecessary processing.

Not all data needs to be replicated into the lakehouse. The Denodo Platform enables live, on-demand access to source systems, giving analytics applications and AI agents current operational context for use cases such as agent responses, personalized services, supply chain decisions, and up-to-date dashboards. This complements Databricks’ strengths in data engineering, batch processing, streaming analytics, and AI.

The Denodo AI SDK simplifies the development of AI and agentic applications by providing governed access to trusted, context-rich enterprise data. Prebuilt interfaces support retrieval, LLM integration, embeddings, and agent workflows while applying consistent security and governance. By separating enterprise data access and integration logic from agent process logic, Denodo reduces custom development, retrieval complexity, model workload, and time-to-value.

With the Denodo Data Catalog, non-technical users gain an intuitive interface to explore, evaluate, and request access to data across the enterprise. Integrated with Unity Catalog, it provides a unified data governance experience with built-in support for endorsements, data quality feedback, and policy enforcement.

As data spans hybrid and multi-cloud environments, the Denodo Platform applies consistent, fine-grained security and access policies at runtime, regardless of where the data resides. Identity-aware controls, row-level filtering, masking, and policy enforcement help ensure that users and AI agents access only the information they are authorized to see—including before sensitive data reaches an AI model.

The Denodo Platform improves query performance through intelligent caching, pushdown optimization, and an embedded MPP engine. FinOps dashboards and AI-assisted optimization help teams manage compute, data movement, and resource usage. By delivering relevant, business-ready context rather than fragmented raw data, Denodo can also reduce unnecessary retrieval, duplicated integration, model workload, latency, and AI processing costs.