AI Solution Architecture for a Med-Spa Chain Unifying Booking, CRM and Membership Data
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Problem
Five vendors, five architectures
A 22-location med-spa group had centralised booking, CRM, membership and point-of-sale systems, and wanted an AI layer across them — no-show prediction, membership churn alerts, campaign timing. But five competing vendor proposals each assumed its own data pipeline, client records were duplicated across systems, and nobody had defined how protected health information would be handled by any model.
Solution
One governed AI reference architecture
We designed a single reference architecture for the group: an event pipeline unifying booking, CRM and POS data into one governed layer, tiered zones separating identifiable health information from modelling data, a shared feature store, and a standard model-serving pattern. We then proved it by shipping the first use case — no-show risk scoring — on the new foundation.
Measurable Impact
What changed after launch
5 disconnected vendor AI proposals replaced by one approved reference architecture
Booking, CRM, membership and POS data from all 22 locations unified into a single governed layer
First pilot — no-show risk scoring — shipped on the architecture within 9 weeks of approval
Estimated integration effort for each future AI use case reduced by roughly 40%
Tech & Tools Used
What powered the build
Ready to Build your Medical Aesthetics & Wellness Business with AI Solution Architecture
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