Med Spas · AI Dev Team
Reply to Instagram DMs Before They Ghost: AI Engineering for Your Med Spa
Med spa growth lives or dies on three workflows your front desk can't keep up with: a flood of Instagram DMs and site form fills that go cold within an hour, custom package math for tox + filler + laser bundles that gets re-done by hand at every consult, and the retreatment nudge for Botox at 12 weeks or filler at 9 months that nobody remembers to send. We embed an AI engineering team into your stack — Boulevard, Aesthetic Record, Symplast, Mangomint, Meta inbox, Klaviyo, Stripe — and ship the connective tissue your team has been faking with spreadsheets and reminder Post-its.
What we build for Med Spas
Triage Instagram DMs and site forms into booked consults within minutes
An AI agent drafts a compliant first reply for every DM and form fill, qualifies on treatment interest and budget, and drops a Boulevard or Aesthetic Record booking link before the lead loses interest. Front desk reviews and sends in one click.
Auto-build treatment-plan pricing for tox, filler, laser, and member bundles
From a quick consult intake (units of tox, syringes of filler, laser areas, membership tier), the tool generates an itemized quote with package and member discounts already applied, and pushes it to the client's portal or text thread.
Trigger retreatment recall at the right window per modality
The system tracks each client's last neurotoxin, filler, laser, or microneedling appointment and fires a personalized rebook nudge at the clinically appropriate interval — 12 weeks for tox, 9 months for HA filler, 4–6 weeks for laser series — straight into SMS or Klaviyo.
How a Build Pod fits
Week one, your Build Pod sits with your owner-operator and lead injector, watches a real consult, and audits where leads, quotes, and recall messages actually live today. We pick the highest-leverage workflow — usually DM response time — and ship a working v1 in two to three weeks against your real Boulevard or Aesthetic Record data, not a sandbox.
From there the pod stays embedded month over month: package-pricing tool next, then the retreatment recall engine, then whatever the practice manager flags in the weekly review. You get a dedicated AI engineering team that learns your protocols, your injectors' preferences, and your membership math — not a project handoff that goes stale the day it ships.
Frequently asked questions
- How to get clients for a med spa?
- The leverage points we automate are the boring ones: instant reply to every Instagram DM and site form, a fast online booker tied to your PMS, and SMS plus email recall at the right retreatment window. Branding and offers still come from you — we make sure no qualified lead waits more than a few minutes for a human-quality reply.
- How long before we see working software in the treatment rooms?
- Two to three weeks for the first workflow live on your real data. We start with whatever loses you the most bookings — usually DM response — and expand from there in weekly increments your team can actually absorb.
- Will this work with Boulevard, Aesthetic Record, Symplast, or Mangomint?
- Yes. We integrate with whichever PMS you already run, plus Meta's inbox, Klaviyo or Mailchimp, and Stripe or your card-on-file processor. We don't ask you to switch systems — the pod builds the glue around what your injectors and front desk already use.
- Who handles HIPAA and before/after photo data?
- Everything we build runs inside your accounts and BAAs, with photos and PHI staying in your PMS or a HIPAA-eligible store you control. The pod signs a BAA and we scope each workflow so client data never leaves vetted infrastructure.
- What happens to the code and tools after the engagement?
- You own the code, the prompts, and the integrations from day one. If you ever pause the subscription, the workflows keep running on your infrastructure — the pod is the team that keeps shipping new ones.
Ready to ship AI for med spas?
A Build Pod gets working AI into your stack in 2–3 weeks. Month-to-month, cancel any time.
Talk to a Build Pod