How I'd build Spa AI
I'd reach for Next.js on the front end, FastAPI for the backend, and Postgres for the database, running on a VPS with Caddy as a reverse proxy. Stripe handles billing, Twilio and Resend handle outreach, and I'd wire direct integrations to Mindbody, Vagaro, and Zenoti APIs. Rough estimate: 280 focused development hours, so around $21k in labor at this rate.
Day-by-day plan
- Day 1: Provision Auth0 schema, database migrations for multi-tenant customers, and basic Stripe webhook listener.
- Day 2: Wire Stripe billing for the three pricing tiers ($249/month base, scaling up for volume), test subscription lifecycle and churn flows.
- Day 3-4: Build the customer onboarding flow, including OAuth connection to Mindbody or Vagaro, ingest sample data, validate the data model.
- Day 5-6: Core retention engine: write the SQL that flags lapsed clients (hasn't booked in 45+ days), segments them by treatment type and frequency, surfaces re-engagement cohorts in the dashboard.
- Day 7: Build the campaign builder UI. Owners pick email templates, SMS messages, scheduling rules, daily send limits.
- Day 8-9: Wire Twilio and Resend outbound channels, add basic event logging so we track opens, replies, bounces.
- Day 10: Set up webhook ingestion from Mindbody and Vagaro so new bookings and cancellations flow into our system in near real-time.
- Day 11-12: Build the customer analytics dashboard. Cohort tables, re-engagement ROI metrics, treatment-level breakdowns, time-to-rebook trends.
- Day 13: Write API documentation, create a runbook for manual troubleshooting, set up monitoring alerts.
- Day 14: Deploy to production, run through a full onboarding with a test customer.
What's hard about this build
Mindbody, Vagaro, and Zenoti each control the API gates tightly. Mindbody requires a formal partnership agreement. Vagaro has aggressive rate limits and a confusing permissions model. Zenoti has a 2-4 week approval process. Getting sandbox access to all three took me three weeks on a previous project. Once you're in, the data models don't align: Mindbody calls them "appointments," Vagaro calls them "bookings," and both return client history in different shapes. Building an abstraction layer that normalizes these APIs without breaking when they push updates is the core technical risk. I'd budget 120 hours just for integration work and another 40 for edge cases - clients with no phone numbers, multiple locations mapped to one account, timezone mismatches in the booking data. Testing is hard without live data, so production issues are almost inevitable. And you're right to worry about the compliance piece: med spas handle health data and PHI; if we store or transmit anything that touches HIPAA, we need a BAA. I'd factor 30 hours for that legal review.
What's fast because of AI
Claude accelerates scaffolding and test coverage dramatically. I use Claude to generate the Postgres migrations, the FastAPI endpoint stubs, and the Next.js component structure - work that normally takes a day, done in hours. For the integrations, Claude enumerates edge cases I'd miss on my own: what if a client books twice in one day, what if the API returns null for phone, what if the location code changes mid-month. It writes the test mocks for each API variant, compressing a week of manual stubbing. Copywriting for the product UI - campaign templates, onboarding screens, help text - Claude drafts in an hour; I refine it in another. And debugging: when a Stripe webhook fails silently or a Twilio rate limit kicks in, Claude helps me trace logs and spot the root cause faster than I'd do it alone. Conservative estimate: AI saves me about 60 hours on this build, which is $4500.
How I'd hand it off
I'd record a 20-minute Loom walkthrough of the entire system: how to connect a Mindbody account, build a campaign, read the metrics dashboard. I'd leave behind a Notion runbook: deployment steps, common errors and fixes, how to manually sync data if the webhook fails, how to rotate Stripe keys. I'd provide 30 days of on-call support through Slack with a 4-hour response SLA. You hit a bug, I fix it or escalate. All credentials go into a shared 1Password vault. I'd leave Linear with open tickets organized by priority, and we'd do a Friday hand-off call to walk through the backlog and known risks.