Analyzing Support Requests
- Consolidated and analyzed twelve months of historical partner support requests.
- Ran intent analysis to group requests into clear, well-defined categories.
- Built step-by-step playbooks and friendly response templates for every category, housed in a governed knowledge base.
Building an AI Agent to Assess and Respond
- Developed an LLM-powered AI agent using Copilot Studio, capable of understanding a request, accessing the knowledge base, and executing the necessary actions.
- The agent extracts key details from each request and classifies it against a known category set, with a confidence score determining whether it can be handled automatically.
- Once classified, it retrieves the relevant playbook via RAG, executes the steps through connected systems, and drafts a reply in the same thread.
Human Oversight and Continuous Learning
- Requests below the confidence threshold were routed to human agents, along with an AI-generated draft reply and recommended next actions.
- Weekly reviews refined the playbooks and training examples, so the system kept improving.