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AI infrastructure introduces a new class of risk: interdependent data, models, identities, and pipelines can fail out of sync, leaving systems operational but no longer trustworthy. At the same time, a growing CIO/CISO disconnect is creating unclear ownership and slowing response when trust is lost. In this session, Commvault will show how to close that gap with a shared control plane approach: governing access, protecting the full AI stack, and recovering systems to a clean, coherent, and trusted state. Jose Gomez, Global Field CTO at Satori (acquired by Commvault in mid-2025), highlighted the company’s evolution beyond traditional backups, with a focus on AI data access governance. This includes managing structured data across environments such as SQL Server, Snowflake, and Databricks, and overseeing its use to train AI models and LLMs. The core objective is to govern data *before* AI agents or humans access it, establishing a new governance control plane to mitigate risks in a rapidly evolving AI landscape.
The new approach to governance centers on a proxy-based application that acts as a Data Access Controller (DAC) and an LLM gateway. This system intercepts data requests from both human users and AI agents, applying real-time policies. Leveraging APIs and a Kubernetes platform, it integrates with identity providers such as Active Directory to manage user access and enforce granular policies, including data classification and redaction of sensitive information. This ensures that even when AI agents act on behalf of users, data access is controlled, preventing sensitive information from entering RAG databases or being inadvertently captured in training logs. The platform offers flexible deployment options, including a fully managed cloud service or customer-hosted Kubernetes, addressing data sovereignty and regional compliance requirements like GDPR by keeping data processing within specified geographic boundaries.
Beyond governance, Commvault emphasizes “trusted recovery” for the entire AI stack. Recognizing that AI applications involve complex interdependencies among data, models, identities, pipelines, and underlying infrastructure, traditional data recovery methods are insufficient. The platform aims to provide comprehensive data protection across all these layers to ensure that, in the event of a compromise, the entire AI system can be quickly restored to a coherent, trusted, and functional state. Commvault positions itself as a critical layer in cyber resiliency, offering visibility and guardrails to manage the dynamic AI environment, balancing business efficiency with robust security and compliance amid rapidly evolving AI models and applications.
Personnel: José Gomez
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