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AI-First MVP · Healthcare

Healthcare Scheduling SaaS

Scalable scheduling and patient communication platform with admin tools, integrations, and AI-assisted message templates.

AI-FIRST MVP
12 weeks
from kickoff to first booking
3
clinical systems integrated
100%
patient comms audit-logged
The challenge

What the client was facing

A healthcare group needed to launch a new digital scheduling service quickly — with proper compliance, integrations into existing clinical systems, and a patient-facing experience that wouldn't embarrass the brand.

What we built

The solution

  • Patient-facing booking flow with multi-channel reminders
  • Provider scheduling and capacity management for admin staff
  • Integration layer for clinical systems and calendar providers
  • AI-assisted message templates: tone, language, jurisdiction-aware
In production

What it looks like

Illustrative screens — actual client UI, branding, and data redacted under NDA.

Healthcare Scheduling SaaSOverview82%Accuracy3.2kItems12Today4.7ScoreTrend
Healthcare Scheduling SaaS — analytics 1 2 3 4 5 6 7 8class ClaimsExtractor: def __init__(self, llm, schema): self.llm = llm self.schema = schema def extract(self, document): prompt = self.build_prompt(document) raw = self.llm.complete(prompt) return self.schema.validate(raw)AI suggestion ▸
AI-first delivery angle

Why AI-first mattered here

AI is used for communication drafting, not clinical decisions. Senior engineers owned data security, audit trails, and the compliance boundary — the line between 'helpful' and 'risky' was drawn clearly.

Technologies

Stack

TypeScript NestJS PostgreSQL OpenAI Twilio Azure

Have a similar problem to solve?

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