Healthcare AI Development,
HIPAA-Compliant by Architecture
We build AI automation for medical practices: patient intake, inbox triage, claims and billing, and clinical documentation support. Self-hosted where PHI cannot leave your network, and scoped against published evidence rather than vendor claims.
Your clinical staff should not be doing admin a machine can do.
In most practices the expensive problem is not clinical. It is the hours that qualified people spend re-typing intake forms, chasing insurance eligibility, sorting a shared inbox nobody owns, and reassembling documentation that already exists somewhere in the record.
That work is high volume, rule-governed, and has a clear definition of correct, which is exactly what automates well. The clinical judgment stays with your clinicians. The retyping does not need to.
The part we will not gloss over: patient data changes the calculation. Where PHI is involved we either keep it entirely inside your network on hardware you control, or we use a service that will sign a business associate agreement covering the functionality you actually use, verified in their own legal terms rather than their marketing.
What you actually get
- ✓ One admin workflow automated, measured, and running in production
- ✓ Patient data either self-hosted or covered by a verified BAA
- ✓ Integration into the record system you already run
- ✓ A written data-flow map showing exactly where PHI travels
- ✓ Documentation and handover, so you are never locked in to us
We publish 21 guides on healthcare AI, including the ones that complicate our own sales pitch.
Everything below this point is the technical detail: the frameworks, models, and architecture we use. If that is not your area, skip it and send us a note instead.
Seven healthcare engineering capabilities.
Built around where practice cost actually concentrates: the front desk, the inbox, and the billing cycle. Every deployment starts with a map of where patient data travels.
Patient Intake & Front-Desk Automation
The front desk is where practice admin cost concentrates and where automation pays back fastest. We build intake that collects history, insurance, and consent before the appointment, validates it against your practice management system, and flags only the records that genuinely need a human to look.
- ✓ Pre-visit intake and insurance capture
- ✓ Validation against your PMS
- ✓ Exception-only staff review
Inbox & Message Triage
Multi-doctor practices drown in a shared inbox nobody owns. We build triage that sorts, tags, and routes clinical and administrative messages to the right person with urgency assessed, so the clinical inbox stops being a queue everyone is afraid to open.
- ✓ Clinical vs administrative routing
- ✓ Urgency and escalation rules
- ✓ Works with Missive, Front, and Help Scout
Claims & Billing Automation
Claims work is rule-governed, high volume, and has an unambiguous definition of correct, which makes it close to an ideal automation candidate. We build coding support, eligibility checks, denial triage, and appeal assembly that pulls the clinical justification from the record rather than asking a human to find it again.
- ✓ Eligibility and coverage checks
- ✓ Denial triage and appeal assembly
- ✓ Coding support with human sign-off
Self-Hosted & On-Premise Clinical AI
When PHI cannot leave your network, the answer is naming the actual software rather than promising "private AI". We deploy open-weight models served by Ollama or vLLM on your own hardware, with a local vector store, so patient data never crosses your boundary and no BAA is required because no third party ever receives it.
- ✓ Ollama / vLLM on your infrastructure
- ✓ Local vector store, zero data egress
- ✓ No third-party BAA needed
EHR & Interoperability Engineering
Most healthcare AI projects stall at the same place: getting data out of the record system. We work across Epic, Tebra, and the open stack, and we build the interoperability layer with HAPI FHIR, Mirth Connect, and Medplum where a direct integration path does not exist.
- ✓ HL7 v2 and FHIR interface engineering
- ✓ Epic, Tebra, OpenEMR, OpenMRS
- ✓ Mirth Connect and HAPI FHIR pipelines
HIPAA & UK GDPR Architecture Review
Compliance is an architecture question before it is a paperwork question. We map where PHI travels, who processes it, which vendors need a BAA, and whether a claimed compliance posture survives reading the vendor's own legal terms. US HIPAA and UK GDPR are genuinely different problems and we treat them that way.
- ✓ PHI data-flow mapping
- ✓ BAA scope and gating review
- ✓ US HIPAA and UK GDPR addressed separately
Clinical Documentation Support
Ambient documentation and draft-reply tools are the most oversold category in healthcare AI, and we scope them with the evidence rather than the pitch. Deployed carefully against the right task they reduce cognitive load meaningfully, which is a real and defensible benefit even where the time saving is smaller than vendors claim.
- ✓ Scoped against published evidence
- ✓ Clinician review preserved by design
- ✓ Measured on burden, not just minutes
Built for practices, not for pitch decks.
Healthcare AI has more marketing than evidence. We work from the published research, name the actual software, and treat US and UK regulation as the separate problems they are.
What "HIPAA compliant" usually means when a vendor says it.
The phrase is doing a lot of work in most healthcare AI marketing. These are the questions that separate a compliant architecture from a compliant-sounding one.
Frequently asked questions.
Is your AI HIPAA compliant?
The honest answer is that HIPAA compliance is a property of an architecture, not of a product. We build two ways: fully self-hosted, where PHI never leaves your network and no third party receives it so no BAA is required, or cloud deployments on services that will sign a BAA covering the functionality you actually use. We check the vendor's own legal terms first, because several popular platforms gate their BAA behind an annual contract value threshold or exclude specific features from its scope.
Can we run AI for our medical practice without sending patient data to the cloud?
Yes, and for many practices it is the better answer. We deploy open-weight models served by Ollama or vLLM on hardware you control, with a local vector store for retrieval, so patient records never cross your network boundary. This removes the BAA question entirely, and it also decouples your jurisdiction from your vendor, which matters if data residency is a requirement rather than a preference.
How much does healthcare AI development cost for a medical practice?
A scoped pilot covering one workflow typically runs $5,000 to $15,000, a departmental build $15,000 to $40,000, and a multi-workflow practice deployment $40,000 upward. Self-hosted deployments carry higher setup cost and lower running cost, which usually pays back within the first year for practices with meaningful volume.
Will AI documentation tools actually save our clinicians time?
Less than most vendors claim, and it is worth knowing that before you buy. Stanford Medicine found in JAMA Network Open that clinicians spent nearly as long on AI-drafted replies as on replies written from scratch, because verifying a draft is real work. The study did find a meaningful reduction in cognitive load and burnout, which is a genuine benefit, and it is the one we scope and measure against.
Can you integrate with our EHR?
In most cases yes, and the effort depends entirely on what your system exposes. We work directly with Epic and Tebra, and across the open-source stack including OpenEMR, OpenMRS, and Medplum. Where no direct integration path exists we build the interoperability layer using HAPI FHIR and Mirth Connect rather than resorting to screen automation, which is far more fragile against a record system.
Do you work with UK practices as well as US ones?
Yes, and we treat them as genuinely different problems rather than applying US assumptions to UK practices. UK deployments are built against UK GDPR with attention to data residency and NHSmail handling where relevant, while US deployments are built against HIPAA with BAA scope verified in writing. Applying one framework to the other is one of the more common and expensive mistakes in this sector.
Not ready to book a call?
Tell us the one manual process eating the most time in your business. We will reply with whether it is automatable, roughly what it would take, and what it would be worth. No deck, no pitch.
Thirty minutes.
We'll tell you exactly
where your ROI is.
No sales deck. No 50-page report you have to pay for before anything gets built. Just a direct conversation about which of your workflows are costing the most and whether AI can fix them. If there's no compelling answer, we'll say so. And it's a conversation with Kash, our founder, not a rep reading from a script, because the person who built this business is the one who should understand yours.