Luma Health AI

Start with a narrow conversation flow that matches Luma Health AI's core capability: AI patient-access and communication platform for scheduling, outreach, intake, reminders, referrals, and healthcare contact-center workflows. Add the minimum business knowledge required, define operating hours and escalation rules, and connect only the calendar, CRM, telephony, or workflow systems needed for the test.

Run realistic calls or conversations covering the normal path and edge cases: interruptions, caller corrections, ambiguous requests, unavailable appointment times, transfers, background noise, and questions outside the knowledge base. Review transcripts, recordings, tool calls, and summaries rather than judging voice quality alone.

Use explicit rules for actions that change bookings, customer records, payments, or other consequential data. Keep a human handoff path available and test what happens when an integration fails or the agent is uncertain.

After the workflow is reliable, expand knowledge and integrations gradually. Monitor resolution rate, transfers, booking accuracy, latency, customer complaints, and cost per handled interaction after major configuration or model changes.