Cloudera, a cloud and data services provider, has partnered with Mistral, a France-based AI lab, to bring Mistral’s AI models into Cloudera’s hybrid data and AI platform. The arrangement is aimed at enterprises that want to use proprietary information for AI applications while keeping control over where that data and the resulting workloads are processed.
The companies will support deployments across public and private cloud environments, on-premises infrastructure, edge locations and air-gapped systems. Cloudera says the integration will cover as much as 30 exabytes of enterprise data and give customers the option to run inference inside their own environments rather than relying exclusively on external AI services.
The partnership comes as data management remains a constraint for corporate AI projects. Cloudera’s Data Readiness Index 2026 found that 89% of EMEA IT leaders reported complete visibility into where their data resides, but only 26% said that the data was fully governed. The company’s regional vice president for Africa, Warren Olivier, also cited a Gartner prediction that 60% of corporate AI projects could fail by the end of 2026 because they lack AI-ready data.
That gap can affect both deployment and operating costs. Cloudera said fragmented data can require additional context in prompts, while untrusted information can push organizations toward larger models. Repeated calls caused by unreliable outputs can add further consumption, while agent-based applications may generate more usage through reasoning, tool calls and repeated processing.
Olivier said access controls remain another obstacle. “In the EMEA findings of our own index, 42% of leaders said complicated access requirements were their primary barrier to using the data they can see, while only about a third have fully integrated data sources across environments."
For customers using Mistral models through Cloudera, the companies say the integration is intended to keep AI workloads closer to the data they depend on. The partnership covers Mistral’s models and tools for reasoning, chat, coding, document intelligence and voice, while Cloudera provides the data management and governance layer around those workloads.
The arrangement also addresses customization. Through Mistral Forge, a system for building models grounded in proprietary knowledge, enterprises using Cloudera’s platform will be able to train and customize AI models with private data inside controlled environments, according to the companies.
“Enterprise AI is entering a new phase where organizations need more than access to powerful models, they need the freedom to unlock specialized intelligence using their data, on their terms,” said Abhas Ricky, Chief Business Officer & GM, Applied AI at Cloudera. “Together with Mistral, we are giving enterprises the ability to run AI where their data lives, customize it with their own intellectual property, and maintain control over their data, infrastructure, and economics. That combination of intelligence and control is essential to moving AI from experimentation into production.”
The companies also plan to work on AI applications at the edge, where disconnected or latency-sensitive environments can limit the use of centralized cloud infrastructure. Mistral’s partnership executive Kamal Brar said the focus is on allowing enterprises to deploy its models without giving up control of their data, infrastructure or intellectual property.
The joint offering will be available through Cloudera’s enterprise sales team and partner ecosystem, with further integrations planned over time.
