Rubrik Rolls Out Industry’s First Semantic AI Governance Engine

Rubrik, a security and AI operations company, unveiled its Semantic AI Governance Engine (SAGE), the data security industry’s first AI governance engine designed to secure and control autonomous agents in real time.SAGE powers Rubrik Agent Cloud, replacing static, manual oversight with intent-driven governance to safely scale the enterprise AI workforce while maintaining total control over agent behavior.Enterprise AI deployment is stalling at a governance bottleneck, as legacy systems rely on deterministic rules that cannot comprehend natural language nor adapt to dynamic and unforeseen actions taken by agents. Rubrik SAGE solves the bottleneck by using Rubrik’s custom Small Language Model (SLM) to interpret the semantic meaning of policies, providing a real-time command center for agentic operations. 

“SAGE marks a pivotal moment in AI security as we shift the focus from if agents can be deployed to how they can be governed at scale,” said Devvret Rishi, GM AI, Rubrik. “With SAGE, we can move beyond simple monitoring to a future where AI helps us govern AI agents. Now, we give CISOs the guardrails they need to let their AI agents run at full speed without compromising the security and integrity of the enterprise.”

AI Powers Rubrik Agent Cloud
SAGE evolves AI security from reactive monitoring to active, semantic enforcement. By understanding the intent behind a policy, rather than just searching for keywords, SAGE ensures agents operate within safe boundaries without stifling their ability to solve complex tasks.

Key innovations within SAGE include:

• Semantic Policy Interpretation: SAGE translates natural language instructions (e.g., “Do not give financial advice”) into machine logic, recognizing context that static filters miss
• Proprietary SLM: Rubrik’s custom SLM outperforms generalized LLMs in accuracy while operating at a fraction of the latency
• Adaptive Policy Improvement: SAGE proactively identifies ambiguous guardrails and suggests refinements to administrators before a violation occurs
• Integrated Remediation: In the event of an agent error, SAGE triggers Rubrik Agent Rewind to instantly undo destructive actions and restore data integrity

Data-Driven Governance
To validate the efficiency of its governance engine, Rubrik conducted a head-to-head benchmark between Rubrik’s custom SLM and OpenAI’s GPT-5.2. In a comparative analysis using a standardized set of user-agent interactions, Rubrik’s custom SLM: 

• Processed messages 5x faster and detected violations correctly more often
• Achieved a higher accuracy rate in detecting policy violations compared to generalized LLMs
• Significantly reduced the compute overhead typically associated with real-time AI monitoring