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The authorization engine for the AI era. Govern users, services, and AI agents with hierarchical scopes, resource policies, and conditional permissions.

Quickstart

Get started in 5 minutes

Core Concepts

Understand the fundamentals

Why Bedrock?

Bedrock solves authorization problems traditional RBAC cannot:

Hierarchical Scopes

Org → Workspace → Project → Environment with full inheritance

Resource Policies

Fine-grained allow/deny on specific resources or collections

Conditional Permissions

JSON Logic expressions for dynamic, context-aware access

AI Agent Governance

Same authorization model for users, services, and AI agents

Multi-tenant Isolation

Complete tenant separation with scope hierarchies

Tag-based Access

Dynamic permissions based on resource and subject tags

How It Works

Learn about Evaluation

Understand how Bedrock decides if an action is allowed

Core Concepts


Quick Example

Set up your authorization structure via the REST API, then evaluate. The engine is read/evaluate-only—all writes go through the API.

Full Quickstart Guide

Complete setup with all features

Use Cases

User Governance

Traditional RBAC for users across your organization hierarchy

Agent Governance

Control what AI agents can access and do within your systems

Multi-tenant Apps

Isolate permissions across tenants with hierarchical scopes

SaaS Platforms

Model complex SaaS authorization with workspaces and projects

AI Agent Governance

As organizations deploy AI agents (LLM-powered assistants, autonomous workflows, MCP servers), they face new challenges: Bedrock treats agents as first-class subjects (registered via the REST API, same as any subject):

Agent Governance Guide

Complete guide to managing AI agent permissions

API Reference

REST API

Complete API documentation for all endpoints

TypeScript SDK

Native TypeScript/JavaScript integration