AI Scheduling Agent for Healthcare Operations

A major healthcare technology company engaged Taller to build an AI scheduling agent on top of its platform using Chiron, demonstrating how AI could automate appointment workflows and surface operational data conversationally.

Healthcare operations involved constant scheduling complexity. Appointments were canceled, patients needed rescheduling, providers had different specialties and availability, and administrative teams had to match the right patient with the right provider at the right time. Without automation, all of this required manual coordination. A single reschedule could mean checking the patient, identifying the appointment, understanding the specialty, finding available doctors in that specialty, comparing schedules, and reviewing provider information. The same friction applied to broader operational questions about patients, providers, schedules, and availability. The client wanted to see how an AI agent could work on top of its healthcare platform: reading its data, surfacing insights, and handling defined scheduling workflows.

Taller used Chiron to build an AI agent integrated with the client’s healthcare platform. The agent retrieved and reasoned over platform data about patients, doctors, providers, appointments, schedules, specialties, and availability. Users could ask natural-language questions and the agent listed the relevant information, from patient and provider details to appointment data and specialty coverage.

A core workflow was appointment cancellation and rescheduling. When an appointment was canceled, the agent could identify the relevant specialty, find doctors or providers in that specialty, check available schedules, and help match the patient to a new appointment, coordinating the steps through a conversational workflow instead of requiring the user to move across multiple screens. The agent could also analyze provider information and schedule patterns, helping users understand availability, specialty coverage, and operational capacity.

Chiron accelerated the build by providing the agentic orchestration layer: the Knowledge Database held the relevant product, API, and workflow context; the planner structured the implementation; engineering agents working through Chiron’s command-line interface (CLI) supported development and integration; and Pelion IoT Platform workflows let multiple agents coordinate around implementation, data-access behavior, workflow logic, and validation.