Role-based access control (RBAC) was built for structured systems - folders, tables, and databases. AI pipelines are different: data is unstructured, free-flowing, and context-driven. Protecto’s CBAC secures AI by meaning, context, and intent.
AI pipelines combine unstructured, dynamic data. CBAC adapts to this complexity by enforcing rules based on meaning, not structure.
Secures agent-to-agent and tool-to-agent communications where sensitive data is exchanged in real time.
In AI, data flows everywhere. CBAC intelligently interprets who is asking, what the prompt is, and the context to apply the right policies instantly.
See why leading enterprises choose Protecto
| Access Control | Access based on roles and where data sits | Access based on roles and what the data means |
|---|---|---|
| Granularity | CoarseAccess to entire tables or files | Fine-grainedProtects specific values, phrases, chunks, documents |
| Understands data | No Relies on column names or file locations. Fails if data is mislabeled or in the wrong place | Yes |
| Context-aware Policy | Rigid | AdaptiveCan handle complex, context-aware policies |
| Enforcement actions | Block or allow | Block, mask, or transform — while preserving meaning for AI |
| Designed for | Legacy appsStructured data, internal systems | AI-first environmentsLLMs, agents, unstructured data |
Mask PII in tickets and chats, but still let AI resolve cases quickly.
Protect PHI in clinical transcripts while ensuring HIPAA compliance and diagnostic accuracy.
Block account details, salaries, or contracts while enabling AI-driven analytics.
Apply tenant- or team-specific rules across agent-to-agent and MCP-driven workflows.
Protecto’s CBAC delivers intelligent, context-aware access control for AI-native workflows - securing sensitive data without breaking accuracy.
This datasheet outlines features that safeguard your data and enable accurate, secure Gen AI applications.