Healthcare engineering capabilities
The systems your practices run on, and how AI has to fit them.
AI features in healthcare only work when the data under them is complete. These are the systems we have integrated with and how the team works.
The team
Who builds it.
Product and clinical workflow analysis
Business analysts who map how the front desk, clinicians and managers work before anything is built, so AI removes work people already do.
AI engineering
Retrieval with citations, document extraction, voice and transcription, and agents with approval steps, evaluated on test sets your team reviews.
Platform engineering
Multi-practice SaaS, role-based access, per-provider billing, cloud on AWS, Azure or Google Cloud, and CI/CD with approval gates.
Quality and accessibility
Regression testing, accessibility testing and release management, so AI features ship without breaking what already works.
Systems
Systems we have integrated with.
Built in client codebases and tested with real test traffic. We scope yours in the Product Review.
| Area | Systems |
|---|---|
| Dental practice management | Dentrix, Denticon, OpenDental, Eaglesoft, NextInLine, NexHealth |
| Veterinary practice management | ezyVet, Vetspire |
| EHR | HL7 and FHIR interfaces |
| Phone systems | GoTo Connect, Jive, Netsapiens, Bandwidth, Mango Voice, Telnyx |
| Scheduling and patient experience | DaySmart, Weave, Kolla |
| Registries and billing | NPI Registry verification; Stripe per-provider billing |
| Cloud and models | AWS (Lambda, S3, Bedrock, Textract), Azure OpenAI and Key Vault, Google Cloud Functions and Pub/Sub |
How the team works
One team across product, AI, platform and quality.
A named lead engineer and US-hours overlap, from the first Product Review to production.
Every engagement
- We test each vendor's API with real test traffic before building on it.
- Every change goes through your pull request review and CI.
- We work in your accounts, with access you grant and can revoke.
- We sign a BAA when the work needs one.
See it on your own product.
Bring one product, workflow or AI feature. In 30 minutes we tell you which of the three ways to start fits, what it would cost to serve per practice and what your customers' privacy review will ask.
Calls run in US Central time. No generic AI presentation: we discuss your product, users and production constraints.