How Do You Roll Out AI Across a Multi-Location Practice?

Prove each system in one office, then roll it out to the rest. RejuvenX, a Florida regenerative medicine and personal injury group, piloted its call tracking system in Tampa before deploying it everywhere, and by March 2025 six AI systems were live in all 11 of its offices, from intake that creates patients and books appointments in eClinicalWorks to transportation requests made inside the EHR.

This field note is drawn from the RejuvenX case study.

What did RejuvenX automate?

RejuvenX's teams were entering intake by hand, writing narrative reports from MRIs, and chasing call outcomes and patient transportation. The six systems Cream Digital deployed each took one of those jobs:

The work ran inside the EHR, using AI voice agents, automations, and robotic process automation, so staff did not re-type patients or switch systems to request a ride.

Why pilot in one office first?

Because every office is a little different, and it is cheaper to find that out once. RejuvenX's call disposition system ran in Tampa first, then went to every office. A pilot shows where the workflow differs from what was written down: a provider who books differently, a front desk with its own shortcut, a call type nobody mentioned. Fixing those in one office means the other ten get a version that already works.

What changes when you scale from one clinic to eleven?

Three things become important that barely matter in one office:

1. One written workflow. Every office should run the same steps and rules, documented the way part two of the Digital Employee Playbook describes. Without it, eleven offices drift into eleven processes.
2. Settings per office. Hours, providers, addresses, and phone numbers differ. They belong in each location's settings, not in eleven copies of the system. The same local detail is what makes a location page worth publishing, covered in whether city pages still work for local search.
3. Alerts that reach the right office. An unsuccessful call or a finished visit is only useful if the alert goes to the team that can act on it, which is why RejuvenX's alerts arrive in Microsoft Teams after each visit.

How does AI fit inside the EHR?

As closely as the EHR allows. At RejuvenX, the intake agent creates the patient and books the appointment in eClinicalWorks, and transportation is requested from inside the EHR. How much an AI system can do inside a given EHR varies by vendor, covered in whether an AI receptionist can book into your EHR.

What should a multi-location group measure?

The same numbers in every office, side by side: calls answered, unsuccessful calls, intake booked, report turnaround, and rides requested. When one office lags, the dashboard shows it, and the fix can be checked against the offices that work. Pricing often changes with locations too, covered in how much an AI receptionist costs. That is how Cream Digital builds AI workflows for groups with more than one location.