Projects / Voice
AI Voice Booking Assistant
I designed a controlled AI booking conversation so a real service business can collect the right details, confirm pricing, and book appointments more reliably.
Problem solved
Missed or unstructured calls left incomplete customer data, unclear service requests, pricing confusion, and unreliable appointment confirmation.
What I built
A 10-stage booking flow with one-question-at-a-time control, pricing confirmation checkpoints, address collection, appointment options, and a professional close.
Technologies used
Prompt engineering, conversational QA, business rules, ChatGPT; n8n / Airtable / Twilio in documented project scope.
Why this matters to an employer
You get hands-on conversational AI operations: define expected behavior, catch failure patterns, fix prompts/rules, retest, and document — the same loop production AI teams need.
Verified outcome
Documented 10-stage Functional Build with published sanitized docs. Addressed 5+ failure classes in testing (loops, repeated questions, order errors, pricing gaps, address handling). No call-volume metrics claimed.
Workflow diagram
Architecture diagram of booking stages — not a live telephony UI screenshot.
Architecture diagram — proprietary prompt text withheld.
Sanitized documentation evidence
Ready to interview? I am available for remote AI Operations, Automation, Technical Support, and AI Implementation roles.