Denodo has released Denodo Platform 9.5, expanding its data layer for agentic AI, analytics, and governed self-service data delivery.
The latest version is designed to provide what Denodo calls active context: trusted business meaning, governed metrics, semantic relationships, live operational data access, and policy controls that AI systems and data consumers can use to act with greater confidence.
The release expands the enterprise knowledge graph within the Denodo Data Marketplace, introduces metric views for governed KPIs, enhances Denodo Assistant, and broadens connectivity across the data and AI ecosystem.
Denodo said enterprise AI initiatives increasingly depend on whether AI agents, applications, and business users can access trusted enterprise context in real time. Data access alone is not enough where organisations need shared business meaning, consistent governance, reusable data products, and controlled access to live operational systems.
The expanded Data Marketplace includes a new 360 graph and asset extensions, allowing organisations to define a broader enterprise knowledge graph. Teams can manage related assets including ETL processes, consuming applications, notebooks, business glossaries, data dictionaries, governance controls, data product contracts, data sharing agreements, AI skills, and technical artefacts.
Jose Carlos Bermejo, head of Data & Analytics at Air Europa, who had access to a public beta version, said: “Denodo’s 360 graph and asset extensions mark a major milestone in the evolution of our data governance model, reinforcing Denodo as the core of our semantic layer and the central hub for governed access to data assets. These new capabilities enable us to enrich, connect, and contextualise our data assets, turning them into accessible, governed, and interconnected data products through the Denodo Data Marketplace. As a result, we can provide business users with a unified, intuitive, and trusted view of data, accelerating the adoption of data as a strategic asset and scaling its governed use across the organisation as part of our broader data democratisation strategy.”
The introduction of metric views addresses a common enterprise problem: different teams often define core measures such as revenue, profit, order count, and customer value in different ways across dashboards, tools, and reports. Denodo Platform 9.5 allows companies to define those measures once in the semantic layer, along with formulas, dimensions, filters, relationships, and documentation.
Those trusted metrics can then be reused across governed data products, business intelligence tools, the Denodo Data Marketplace, and AI powered experiences. The aim is to reduce conflicting KPIs and give downstream users greater confidence that decisions are based on consistent live data.
The release also advances Denodo Assistant through improved reasoning and disambiguation. The assistant now supports a more conversational development workflow as users explore metadata, generate VQL, refine query logic, and troubleshoot issues. It can guide users through follow up prompts and contextual feedback without requiring them to know exact syntax or field names.
Connectivity has also been expanded, including support for unstructured data, Databricks, Azure AI Search, vector search indexes, Delta tables, Databricks environments, and more efficient use of the Denodo Lakehouse Accelerator with Iceberg.
Alberto Pan, chief technology officer at Denodo, said: “Agentic AI is changing what organisations require from their data infrastructure. AI systems need to understand business context, work with trusted metrics, access live operational data, and operate within clear governance controls. Denodo Platform 9.5 helps organisations deliver the trusted active context that AI, analytics, and data consumers across the entire enterprise need to act with confidence.”
The release lands as companies look to replace experimentation with governed AI deployment. Poor, incomplete, or inconsistent data continues to slow major programmes, as examined in data quality delays strategic projects. The same problem becomes more acute when AI agents are expected to act on enterprise data without constant human mediation.
Agentic AI changes the data infrastructure question. Traditional analytics tools present information for humans to interpret. AI agents may recommend, trigger, or execute actions. Poor context therefore carries a higher operational risk. If an agent misunderstands a metric, uses stale information, ignores governance controls, or draws from the wrong system, the error can move quickly into operational decisions.
Semantic layers, knowledge graphs, and governed data products are becoming more important because they provide shared definitions and relationships that help both humans and machines understand what data represents. Without that layer, enterprise AI risks producing confident answers from fragmented or conflicting sources.
The market for data infrastructure is also being reshaped by the rise of lakehouses, vector search, unstructured data, and AI development environments. Companies rarely operate from one clean data estate. They need access across legacy systems, cloud platforms, analytics tools, operational databases, and document repositories. Denodo’s proposition is that a logical data layer can reduce duplication while maintaining governance.
Adoption will require more than a software upgrade. Businesses still need agreement on definitions, ownership, data quality standards, and accountability. Trusted metrics depend on governance decisions as much as technical configuration.
Denodo Platform 9.5 gives enterprises more tools to connect AI systems with governed context. Its value will depend on whether organisations use those tools to simplify decision making, reduce metric confusion, and keep AI deployment within clear operational boundaries.
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