Role Based Access Control Rbac With Multi User Collaboration

via “agent collaboration and sharing with role-based access control (rbac)”

AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

Unique: Implements role-based access control (viewer/editor/owner) at the API level, with version history tracking who made changes. Shared agents are discoverable in the user's workspace, and access can be revoked without deleting the agent.

vs others: More granular than cloud-hosted agents (OpenAI Assistants) because role-based access is explicit; more transparent than code-based frameworks because access control is enforced at the API level and visible in the UI.

via “role-based access control (rbac) with fine-grained permission assignment”

Enterprise SSO, SCIM, and identity management API.

Unique: Provides server-side RBAC evaluation integrated with WorkOS's identity system, allowing permission checks to be decoupled from your application's database and eliminating the need to maintain separate role/permission tables

vs others: More integrated with enterprise identity than building custom RBAC (no separate permission database needed) but less flexible than dedicated authorization services like Oso or Authz for complex attribute-based policies

via “collection-level access control with role-based permissions”

Scalable vector database — billion-scale, GPU acceleration, multiple index types, Zilliz Cloud.

Unique: RBAC is enforced at query execution level (QueryCoordinator), not just at API gateway; prevents privilege escalation through direct node access. API key support enables service-to-service authentication without user credentials

vs others: More granular than Pinecone's API key model; simpler than Weaviate's OIDC integration but sufficient for most use cases

via “team-workspace-management-with-role-based-access-control”

Metadata store for ML experiments at scale.

Unique: Integrates RBAC with experiment-level operations (e.g., 'can promote models to production') rather than just workspace-level access, enabling fine-grained governance of model deployment decisions

vs others: Provides more granular permission control than Weights & Biases' team-level access and includes built-in audit logging unlike MLflow's minimal access control

via “team-collaboration-with-role-based-access-control”

Unified LLM DevOps with API gateway, routing, and observability.

Unique: Implements RBAC with audit logging and team-scoped resources, rather than all-or-nothing access, enabling organizations to grant granular permissions without sharing credentials

vs others: More secure than shared credentials because RBAC enables fine-grained access control and audit trails provide accountability for changes to production configurations

via “workspace and organization management with role-based access control”

Build, deploy, and orchestrate AI agents. Sim is the central intelligence layer for your AI workforce.

Unique: Implements multi-tenant workspaces with role-based access control, organization-level settings (branding, SSO, billing), and email-based user invitations with expiring links — enabling team collaboration with fine-grained permission management

vs others: More flexible than single-user systems because it supports team collaboration; more secure than flat permission models because roles enforce least-privilege access

via “collaborative team annotation with role-based access control”

Open-source text annotation for NLP tasks.

Unique: Uses Django's permission framework with project-level role assignment, where roles are enforced at the serializer level in REST endpoints — each API call checks user.has_perm() before returning data, ensuring no leakage of unauthorized annotations

vs others: More lightweight than enterprise platforms like Labelbox (no custom role hierarchies) but more structured than Prodigy's single-user focus; better for teams needing basic RBAC without complex permission matrices

via “role-based access control (rbac) with multi-user collaboration”

AI visual development with design-to-code and CMS.

Unique: Provides predefined roles (Admin, Developer, Designer, Editor) with role-specific permissions for code generation, visual editing, and publishing. Enables non-developers (designers, product managers) to collaborate without full code access.

vs others: More granular than simple owner/viewer permissions because it supports multiple specialized roles; less flexible than custom RBAC systems but simpler to set up and manage.

via “rbac and authentication with role-based access control”

Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search

Unique: Implements RBAC at Proxy service layer with Root Coordinator metadata management, supporting custom role definitions and granular collection/partition-level permissions with immediate revocation without cluster restart

vs others: Provides more flexible RBAC than Pinecone's API key-based access through role definitions, while maintaining simpler deployment than Elasticsearch's complex security model

via “multi-user workflow collaboration with project-based access control”

Workflow automation with AI — 400+ integrations, agent nodes, LLM chains, visual builder.

Unique: Implements project-based organization with role-based access control, enabling workflows to be grouped logically with shared credentials and permissions. Audit logs track all user actions for compliance.

vs others: More granular than Zapier's team sharing because project-based organization enables department-level separation, and audit logs provide compliance visibility.

via “role-based access control with granular permission enforcement”

AI platform for building internal business apps.

Unique: Enforces permissions at the server-side query layer before data is serialized, combined with attribute-based rules that evaluate user properties dynamically, ensuring that permission changes take effect immediately without requiring application redeployment

vs others: More granular than Airtable's sharing model because it supports field-level and record-level restrictions, and more flexible than Retool because it includes built-in ABAC evaluation rather than requiring custom middleware

via “user management and role-based access control”

SoTA production-ready AI retrieval system. Agentic Retrieval-Augmented Generation (RAG) with a RESTful API.

Unique: Implements RBAC at the API endpoint level using FastAPI dependency injection, enabling declarative permission checks without boilerplate. User isolation is enforced through query filters, ensuring users only see documents they have access to.

vs others: More integrated than adding external auth (Auth0, Okta) because permissions are enforced within R2R; simpler than implementing custom RBAC because roles are pre-defined and configurable.

via “authentication and authorization with role-based access control”

AI Observability & Evaluation

Unique: Implements RBAC at both API and database layers, ensuring authorization is enforced consistently across GraphQL, REST, and direct database access. Supports both API key and OAuth2/OIDC authentication mechanisms.

vs others: Role-based access control enables multi-tenant deployments where different teams can access the same Phoenix instance with appropriate data isolation, unlike single-user deployments.

via “role-based access control (rbac) with permission domains and multi-tenancy”

Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database​.

Unique: Implements permission domains enabling fine-grained access control at collection and object level, not just role-based. Multi-tenancy is first-class with tenant-specific RBAC policies and data isolation.

vs others: More granular than Pinecone's API key-based access because it supports role-based permissions; better multi-tenancy than Milvus because tenant isolation is built-in rather than application-level.

via “user management and role-based access control with multi-tenancy”

基于AI的工作效率提升工具（聊天、绘画、知识库、工作流、 MCP服务市场、语音输入输出、长期记忆） | Ai-based productivity tools (Chat,Draw,RAG,Workflow,MCP marketplace, ASR,TTS, Long-term memory etc)

Unique: Implements organization-level multi-tenancy with RBAC scoped to specific resources (conversations, knowledge bases, workflows, tools), enforced at the API layer through permission checks. Supports both role-based and resource-based access control patterns.

vs others: Provides built-in multi-tenancy and RBAC rather than requiring external authorization services (Auth0, Okta), reducing operational complexity for self-hosted deployments.

via “collaborative-experiment-sharing-and-access-control”

Neptune Client

Unique: Implements workspace-level RBAC with separate API keys per project, allowing fine-grained credential management and audit trails without requiring a separate identity provider

vs others: More granular than MLflow's basic authentication because it supports role-based permissions and audit logging, making it suitable for regulated environments requiring compliance tracking

via “role-based access control (rbac)”

Auth0 delivers a flexible identity and access management solution, offering authentication, authorization, and secure login flows to help developers protect applications across various platforms effectively

Unique: Offers a policy-driven model for RBAC that allows for dynamic role assignment and integration with existing user databases.

vs others: More customizable than AWS IAM due to its user-friendly interface and ease of integration with various applications.

via “role-based-access-control-and-team-collaboration”

Open-source LLMOps platform for prompt management, LLM evaluation, and observability. Build, evaluate, and monitor production-grade LLM applications. [#opensource](https://github.com/agenta-ai/agenta)

via “role-based access control with multi-tenant organization support”

Label Studio annotation tool

Unique: Uses Django's built-in permission system extended with custom organization-level mixins (label_studio/organizations/mixins.py) to enforce multi-tenant isolation; audit trail is automatically captured via Django signals without explicit logging code

vs others: More granular than Prodigy's single-user model; simpler than Labelbox's complex permission hierarchy because roles are standardized across projects

via “team collaboration and role-based access control”

[Documentation](https://docs.airplane.dev/?utm_source=awesome-ai-agents)

Unique: Provides built-in RBAC and audit logging for workflow collaboration, with role-based permissions and change tracking, versus generic project management tools that lack workflow-specific access control

vs others: More secure than shared scripts or spreadsheets because access is controlled and audited, versus ad-hoc sharing that lacks visibility and accountability