Cloudera has partnered with French AI company Mistral to help enterprises build and run AI applications within their own secure data environments, according to a September 10 release from San Jose, California.

The partnership combines Cloudera’s hybrid data and AI platform with Mistral’s models and tools. Customers will be able to deploy Mistral’s technology across public and private clouds, on-premises infrastructure, sovereign environments, edge locations, and air-gapped networks.

Abhas Ricky, Chief Business Officer and GM, Applied AI at Cloudera, stated in the release: “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.”

Why trusted data is becoming the AI advantage

The partnership is relevant to chief data officers (CDOs) because it places data governance at the centre of enterprise AI deployment. Keeping data within a controlled environment can help organizations address security, privacy, data-residency, and compliance concerns. But it does not remove the need for strong governance.

Cloudera’s Data Readiness Index 2026 found that 89% of surveyed IT leaders across Europe, the Middle East and Africa had visibility into where their data resides, but only 26% said the data was fully governed. A further 42% identified complicated access requirements as the main barrier to using data they could locate.

For CDOs, the practical priorities are to:

• Ensure data is accurate, discoverable, permissioned, and fit for specific AI use cases.
• Extend governance to models, prompts, agents, and outputs.
• Decide which workloads belong in public cloud, private infrastructure, and sovereign environments.
• Evaluate models not only on performance, but also on control, cost, security, and deployment flexibility.

Enterprise AI readiness depends on whether an organization can securely connect AI models to accurate, governed data while maintaining control over access, processing, and outputs.