Internal and External AI Agents

Role-Based Retrieval-Augmented Generation (RAG) System for Enhanced Data Security

In an era where AI-powered content generation is transforming industries, securing access to knowledge sources is critical. Our Role-Based Retrieval-Augmented Generation (RAG) System ensures AI retrieves and processes data according to user roles, maintaining confidentiality and control over sensitive information.

Our system integrates AI-driven retrieval with role-based access control (RBAC) to filter and generate responses based on user permissions.

1. Internal Users (Staff Members) → Gain access to private, high-value knowledge sources for advanced AI responses.

2. External Users (Non-Staff/Public) → Restricted to general or public datasets, ensuring controlled AI outputs.

The AI Engine dynamically processes queries, retrieving only the information authorized for the user’s role. This prevents exposure of sensitive data while maintaining efficiency in knowledge retrieval.

Many businesses must regulate AI-generated content based on data sensitivity and user roles. With Role-Based RAG, you can:

1. Control AI Access to Data: Restrict AI-generated content to appropriate user roles. 

2. Prevent Unauthorized Knowledge Leaks: Ensure AI only retrieves relevant, approved data sources. 

3. Improve Compliance & Governance: Align AI responses with security and regulatory policies.

Our system supports multiple user roles, not just internal vs. external. Whether you need granular permissions for departments, teams, or specific personnel, Role-Based RAG adapts to your needs.

Enhance your AI capabilities with secure, role-based knowledge retrieval. Contact us to implement a Role-Based RAG system tailored to your organization’s needs.