Voice agents don’t fail because of the LLM, they fail because backend APIs are too chatty, too slow, and too data-centric. In voice, every extra roundtrip is audible.
In this session we share lessons learned from a real project integrating an AI voice agent with Dynamics 365 Customer Service and Dataverse as the system of record. We’ll present architecture and API design patterns that make voice interactions fast and reliable: bundling domain logic into “agent-ready” Custom APIs, returning pre-formatted plain-text snippets that a voice agent can speak directly to the caller, and defining stable business contracts instead of CRUD-style entity calls.
We’ll walk through concrete building blocks: a caller verification pattern where the agent asks for ZIP code and date of birth and validates them against Dataverse; and a case-creation pattern where the agent turns conversation context into a structured service request in Dynamics, while keeping latency budgets, security, and operability in mind.