Luna AI Local
Service Design · Workflow Prototyping
A local service-business demonstration exploring missed-call recovery and a structured acquisition journey, from an initial interaction to a prepared handoff.
- My contribution
- Product direction & AI-assisted building
- Project status
- Local demonstration · Simulated data & deterministic responses
- Use case
- Local service businesses
- Demonstration
- Response & acquisition
- Stage
- Private local demo
Consider what happens after the inquiry.
A service business needs more than another lead notification. It needs context, a useful next step, and a reliable handoff. I used that problem to direct Luna AI Local, exploring an HVAC missed-call response journey alongside an internal workflow for researching and preparing prospective customer conversations.
Make the journey concrete.
My contribution is product direction and AI-assisted building: defining the stages, the information needed at each step, and the operator’s view. The local demonstrations cover qualification, bounded follow-up, conversation history, and simulated booking, as well as opportunity research and preparation of outreach material.
Prototype behavior before live delivery.
The current demonstration uses fictional data and deterministic responses. Messages are captured locally rather than delivered to recipients; video and calendar actions are simulations. This makes the workflows inspectable while keeping the demonstration distinct from an operating customer-response service or a live AI provider integration.
Learn through visible decisions.
Luna is a private local demonstration, not a live pilot. The work illustrates how I translate a business problem into testable product behavior, with clear operator context and defined stopping points. Provider integration and operational readiness remain future work; no customer acquisition, booking, or revenue result is claimed.