Q: What are the supported and recommended steps to integrate an external Python-based AI application with Freshdesk using REST APIs, and are there any limitations on request frequency, payload size, or response time for such integrations?
Why this matters:
Confirms feasibility, performance limits, and API best practices before AI integration.
Authentication & Security Model
Q: What authentication mechanisms are officially supported for external applications (API Key, OAuth 2.0), and what is the recommended approach for securely authenticating a Python backend without exposing credentials on the client side?
Why this matters:
Critical for enterprise-grade security and compliance.
Q:Which AI logic is recommended to run inside the Freshdesk Custom App (client-side) versus an external Python service, and are there any restrictions on invoking external APIs from Freshdesk apps?
Why this matters:
Helps us to design a clean, compliant architecture.
Q:What ticket fields, customer data, and conversation content are permitted to be sent to an external AI system for processing, and are there any data masking, consent, or compliance requirements we should follow?
Why this matters:
Avoids data-leakage and legal issues when using LLMs.
Q:Are there any requirements or recommendations for hosting external Python AI services (e.g., IP allowlisting, TLS version, public vs private endpoints), and how does Freshdesk validate or whitelist external services?
Why this matters:
Ensures smooth production deployment and avoids blocked API calls.
Q: Are there any reference architectures or best-practice examples for A