@Saravanan M ⚠ Below is a GenAI-powered answer.

All generated answers require validation against the provided references (which you can find yourself by searching on docs.pega.com).

Here is a comprehensive overview of the security architecture.

The security implementation operates on multiple layers:

1. Data Encryption and Transit Security
   • All data at rest is encrypted using 256-bit AES encryption
   • HTTPS (TLS) is used for secure data transmission between systems
   • Secure TLS connectivity can be configured for external REST or SOAP services through Dev Studio
2. Data Protection Mechanisms
   • Prompts and completions are not accessible to other Pega clients
   • No data retention in external models - the LLM models used are stateless
   • Prompts and completions are never used to improve external models
   • Role-based access control ensures only authorized users can manage, view, or use the data
3. Knowledge Buddy Specific Security
   • Secure content ingestion practices protect data during transfer
   • REST APIs for content ingestion and querying are secured through access roles
   • Layered security approach with multiple security checkpoints:
     • Pega Knowledge articles level
     • Data sources level
     • Data chunks level
     • Knowledge Buddy cases level
4. Authentication and Access Control
   • Robust role-based security at multiple levels
   • Access roles define who can create, view, and use data sources
   • Ask Buddy auditing cases are generated for monitoring and tracking API usage
   • Each interaction is logged for security audit purposes

For more detailed information, you can refer to the following documentation:

• Security standards for Pega Cloud
• Pega GenAI data security in Pega Cloud
• Knowledge Buddy Security Implementation

@JamesCarstairs if you need to add anything here, feel free to do so.