A Pan-Enterprise Intelligent Operating Layer

Overview: No centralized algorithm to optimize chair utilization across multiple offices, each with unique provider schedules, procedure durations, and geographic patient demand.

Results: Multi-agent scheduling agent that ingests real-time availability from every PMS, applies enterprise-level rules (e.g., balance load, minimize patient travel), and automatically books appointments into the optimal slot across the entire organization.

Overview: Each office runs its own recall campaign with different cadences, templates, and compliance rules, leading to inconsistent patient outreach and missed revenue.

Results: A unified recall agent that pulls lapsed patient lists from all connected PMS systems, applies a single enterprise recall protocol (with local overrides), and executes omnichannel campaigns while tracking consent centrally.

Overview: Acquired offices use different billing modules or RCM tools, making it impossible to automate eligibility checks at scale.

Results: A verification agent that standardizes insurance data ingestion from multiple PMS and payer portals, runs batch or real-time eligibility checks, and returns structured results to each office’s native system—without custom integrations per location.

Overview: Patients often need to move between offices (e.g., ortho to general), but no system exists to transfer records, schedule the next visit, or notify both front desks.

Results: A workflow orchestration agent that, upon a transfer request, pulls the patient record from the source PMS, creates or links the record in the destination PMS, books the appointment, and notifies both teams—all in real time.