The discovery phase is done and the architecture decisions are in place; now it is time to turn the plan into a fully functional, production-grade AI voice agent hosted in the cloud. The agent’s only job, for its first release, is to pick up inbound calls and guide English-speaking callers through an appointment-scheduling flow. Callers must be able to interrupt, change their minds mid-sentence, or ask clarifying questions, and the conversation should continue naturally with minimal latency. Whenever the agent loses context, it must fall back gracefully rather than stall or loop. I will provide the telephony entry point, access to our calendar API, and the conversation design we approved during consulting. You will own the end-to-end implementation: speech recognition, NLU, dialogue management, text-to-speech, graceful error handling, logging, and deployment to the chosen cloud stack. Unit tests, load tests, and a short piece of hand-off documentation are part of the final delivery. Acceptance criteria • A caller can schedule, reschedule, or cancel an appointment from start to finish without human intervention. • Average round-trip latency stays below one second. • Agent recovers from three defined edge cases (silence, over-talk, unexpected question) using the fallback logic we supply. • Code, configuration, and README are pushed to our private repo and pass the provided CI pipeline. If you have shipped voice agents to production before and can demonstrate the same here, let’s get started.