Permissions for AI-native apps
Most AI apps don't ship. Permissions are the problem.
LLMs should make your apps smarter, but authorizing LLMs is hard:
Data flows span multiple systems and steps (RAG, APIs, embeddings).
LLMs don’t enforce rules, they interpret them.
LLMs need broad access to generate useful responses, but must only act on what a specific user is allowed to see or do.
Without dynamically and tightly scoped permissions, agents will do things they shouldn’t.
Fine-Grained Permissions, Built for AI
Oso lets you define permissions in one place and enforce them everywhere—across apps, RAG pipelines, and autonomous agents:
- Enterprise search returns only what a user is allowed to see.
- RAG workflows apply access checks at retrieval.
- AI agents act on behalf of real users, with tightly scoped permissions and full audit trails.
Built for AI
The permissions layer for apps, agents, AI
Agent-Aware ReBAC
Model user-to-agent relationships for impersonation, delegation, and multi-agent coordination
Retrieval Filtering
Ensure AI pipelines (search, RAG) return only the data a user is authorized to access
Policy Testing & Explainability
Trace and debug access decisions across agent actions and complex data flows
Compliance & Auditing
Maintain a central policy with full audit trails of agent activity and low-latency enforcement
