Global data management firm, Denodo, has launched Denodo Platform 9.4, the latest version of its data management platform designed to help organisations scale agentic and generative artificial intelligence systems with reliable access to governed, real-time data.
The new release strengthens Denodo’s position as a data infrastructure provider for companies seeking to move beyond early AI pilots and proof-of-concept projects into production environments. The platform introduces new capabilities aimed at improving how enterprises access, govern and analyse data across complex systems.
As businesses accelerate their adoption of artificial intelligence, many are discovering that the success of AI initiatives depends heavily on the quality, accessibility and governance of the data powering those systems.
Without unified access to trusted datasets, shared semantic frameworks and enterprise-wide governance policies, AI deployments often struggle to deliver consistent or meaningful business outcomes.
Denodo Platform 9.4 seeks to address those challenges by providing new features tailored to three key groups within organisations: AI teams, data engineering teams and business users.
What you need to know
For AI teams working on advanced analytics and machine learning projects, the platform introduces secure integration with vector databases, a technology increasingly used to power modern AI applications.
This integration enables unified access to structured, semi-structured and unstructured data, including documents, text embeddings, images and other digital content, through a single logical data access layer.
The platform also supports the Model Context Protocol (MCP), allowing compatible AI agents to query enterprise data securely while governance teams retain oversight of how the information is used.
According to Denodo, these capabilities allow organisations to build AI systems grounded in trusted, real-time data, reducing the risk of inaccurate outputs while maintaining compliance with internal and regulatory policies.
Faster performance for data engineering teams
Denodo Platform 9.4 also introduces improvements designed to help data engineering teams accelerate analytics workloads and optimise infrastructure resources.
A key addition is the Lakehouse Accelerator, which leverages the open-source Velox execution engine to significantly improve query performance across lakehouse environments.
The company says the technology can deliver up to four times faster query speeds, alongside improved CPU and memory efficiency and greater scalability for organisations running complex AI and analytics workloads.
These enhancements are intended to help companies extract more value from existing data lakehouse architectures, enabling faster insights while reducing the cost of supporting growing numbers of users and AI applications.
Conversational AI interface for business users
Beyond technical teams, Denodo is also focusing on improving data accessibility for non-technical professionals.
The latest platform introduces a conversational AI interface embedded within the Denodo Data Marketplace, allowing business users to interact with enterprise data through natural language queries.
Rather than requiring specialised knowledge of database structures or analytical tools, users can ask multi-step questions and explore datasets through a conversational interface.
The system also provides transparency into how queries are processed and offers guidance when user intent or context is unclear. According to the company, this approach helps organisations democratise data access while preserving governance and data consistency across departments.
“Organizations are increasingly focused on turning AI ambition into real, operational outcomes. Denodo Platform 9.4 is designed to support that shift by strengthening the data foundation across data teams, AI teams, and business users alike,” said Alberto Pan, Chief Technology Officer, Denodo.
“By combining performance, governance, and intuitive access to live data, we help customers move from AI experimentation to trusted, production-ready AI that can truly differentiate the business.”
Data infrastructure becomes central to AI success
As companies invest heavily in artificial intelligence technologies, the role of data infrastructure is becoming increasingly critical.
Many organisations have discovered that deploying advanced AI models alone is not enough; success often depends on whether those models can access accurate, well-governed data in real time.
By focusing on unified data access, governance and performance optimisation, Denodo is positioning Platform 9.4 as a foundational layer for companies seeking to operationalise AI at scale.
With enterprises across sectors exploring the use of agentic AI systems, generative AI models and advanced analytics, the demand for reliable data platforms capable of supporting these technologies is expected to grow significantly in the coming years.
Denodo’s latest release reflects that shift, aiming to provide organisations with the infrastructure required to transform AI experimentation into trusted, enterprise-grade production systems.
Talking Points
It is noteworthy that Denodo is focusing on access to reliable, governed data. While many organisations are experimenting with artificial intelligence, the real barrier to scaling AI often lies in fragmented data systems and inconsistent data governance.
By introducing capabilities such as secure integration with vector databases and support for the Model Context Protocol, Denodo is positioning its platform as an infrastructure layer that can help organisations connect AI models directly to trusted enterprise data sources.
At Techparley, we see how the success of AI adoption increasingly depends on the strength of the underlying data architecture. Platforms like Denodo that prioritise unified data access, governance, and performance optimisation could play a crucial role in helping organisations move from isolated AI experiments to real operational deployments.
The addition of a conversational interface for business users is also significant. Allowing non-technical teams to interact with enterprise data through natural language could accelerate data-driven decision-making while reducing reliance on specialised technical teams.
As enterprise AI continues to evolve, solutions that bridge the gap between data management and AI deployment will become increasingly important. With its latest platform release, Denodo is positioning itself to play a central role in enabling organisations to operationalise both agentic and generative AI at scale.
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