AI Teams
Build AI applications that respect data boundaries and scale to billions of documents with proven authorization infrastructure.
Keep your AI within data boundaries
Every AI response respects user permissions with accurate, instant, and scalable access filtering.
Permission-aware retrieval
Filter document retrieval before context reaches your LLM. AI responses never include information from documents the user isn't authorized to see, maintaining data boundaries at retrieval time.
Pre-filter document ingestion
Filter data sources to include only authorized documents before generating embeddings and storing them in your vector database. Prevent unauthorized data from entering your pipeline in the first place.
Enterprise connectors with real-time sync
Replicate permission models from Google Drive, OneDrive, SharePoint, and Box without custom code. AuthZed's flexible schema expresses any permission structure in a single unified system and keeps it current as permissions change. Revocations are reflected immediately across your AI pipeline.
Agent access boundaries
Share specific resources and tools with AI agents explicitly. Agents only access what they are granted, making permissions the security boundary for autonomous AI workflows.
"We decided to buy instead of build early on. This is an authorization system with established patterns. We didn't want to reinvent the wheel when we could move fast with a proven solution."
— Member of Technical Staff, OpenAI
Your AI is only as trusted as your access controls
When enterprise customers connect their data, they expect their permissions to be respected. AuthZed makes sure your AI never surfaces information users aren't authorized to see, at any scale.
Filter at retrieval speed
Permission checks as fast as single-digit milliseconds. Authorization never becomes the bottleneck in your AI pipeline. For bulk filtering, AuthZed's Materialize feature pre-computes results so queries across millions of documents return instantly, making permission-aware RAG performant at scale.
Model any permission structure
Express Google Drive's folder inheritance, OneDrive's sharing semantics, Box's collaboration rules, or your custom permission model in a single declarative schema. Add new integrations by updating the schema. No code changes, no re-architecture, no per-customer logic scattered through your codebase.
Operate at proven scale
37 billion documents with fine-grained permissions. This isn't theoretical capacity. It's what AuthZed handles in production for the world's largest enterprise AI deployments, with reliability that eliminated most SRE burden for the OpenAI team.
Built for the AI you ship
Enterprise AI and Copilots
Power AI assistants that integrate with enterprise knowledge while respecting existing permissions. Employees only see information from documents they're authorized to access, maintaining trust in AI outputs.
AI Infrastructure and Platforms
Build multi-tenant AI services with data isolation guarantees. Multiple customers and use cases run on shared infrastructure without compromising security boundaries or leaking data across tenants.
Developer Tools and Platforms
Secure access to code repositories, secrets, deployments, and infrastructure with fine-grained controls. Supports the complex permission requirements of platform engineering teams building AI-powered developer tools.
Data Platforms and Analytics
Enforce row-level and column-level permissions across data warehouses and analytics platforms. Users and models query exactly the data they should see, with performance that doesn't degrade as permission complexity grows.
Where does your authorization stand?
Evaluate your infrastructure across performance, agility, and risk — get a personalized maturity score with actionable next steps.
See what AuthZed can do for your AI.
Learn how AI teams build permission-aware applications at scale.