Blog Post
Building an Agentic, AI-Powered Helpdesk with Agents Framework, Azure, and Microsoft 365
This is a really solid breakdown of an agentic helpdesk architecture, especially the separation between ingestion and async processing.
One thing I’ve seen in real-world implementations is that the decision layer becomes more powerful when combined with CRM-level automation. Mapping AI decisions to lead lifecycle stages or customer intent scoring can significantly improve response prioritization.
Also curious, have you tested adding feedback loops like user satisfaction or resolution success back into the agent to improve future decision accuracy?
I’ve been exploring a similar approach around https://growthlocal.com.au workflows and system integrations.
Would be great to hear your thoughts on scaling the decision-making layer further.
Hello syedaayesha ! Thank you for the support ! There is a study coming up for scaling btw! I can give you my 2 cents however: Break the decision loop into layers and Route decisions to different models . We cannot rely ona single llm as you already know so paired with an Orchestrator , multiple tooling and more than one LLms based on context-action-outcome you can scale x times more . Trade off ? yes the complexity increases that's why I am very in favor of MCP , Dual MCP , and the newest MCP Apps !