Digital health software built for integration and audit from the first commit
Willowark builds the integration and data layer for digital health products: HL7 v2 and FHIR interfaces to the systems your customers run, intake and scheduling engines, prior-authorization and clinical document automation, and the access logging and data controls that must exist before the first health system security review. What we remove is the engineering distance between a product that works in a pilot and one that survives interface review.
Integration is built against a canonical internal model with per-site adapters, because two hospitals running the same EHR still send different messages, and it ships with a conformance harness driven by synthetic data. PHI is handled deliberately: minimized at collection, encrypted in transit and at rest, reachable only through least-privilege identities, and recorded in immutable access logs. To be direct — we practice HIPAA-aware engineering and build to your control requirements. Willowark holds no certifications and attests to nothing on your behalf.
A first engagement in digital health is usually one interface or one workflow: the HL7 feed a pilot site needs before go-live, the intake process that still runs on faxes, or the access logging a security review flagged. The constraint that shapes all of it is that PHI raises the cost of every shortcut, so we work in your environments under your business associate terms, test against synthetic records, and treat the customer's interface team and change windows as the schedule. What we hand back is configuration and adapters your team can repeat at the next site.
Reviewed
Sound familiar?
If you've said any of these, we should talk.
“Every health system integration turns into a months-long custom project.”
We build an integration layer designed for variation: a canonical internal model, HL7 v2 parsing and normalization, FHIR resource mapping, and per-site configuration that captures differences instead of forking code. A conformance harness with synthetic messages validates each site before go-live, so a new customer becomes configuration plus a small adapter.
“Prior authorization and referral paperwork consume our operations team.”
We build document automation with a human in the loop: ingest faxes and PDFs, extract structured fields with confidence scoring, route low-confidence items to a review queue, and log every action against its source document. Clinical judgment stays with clinicians; transcription and routing is what gets automated.
“Security review keeps stalling deals that are otherwise closed.”
What stalls those reviews is usually engineering evidence rather than policy language: environment separation, key management, immutable access logs, least-privilege identities, documented data flows, and enforced retention. We build those properties into the system. Your compliance team owns the attestations; we make sure the code supports them.
“Scheduling and intake are held together by spreadsheets and phone calls.”
We build constraint-aware scheduling: provider availability, location and modality, licensure by state, appointment duration and buffer rules, with reminders and automatic waitlist backfill. The AI operating software we built for Jaguar Land Rover's training organization solved the same class of scheduling and logistics problem in a different industry.
“Eligibility checks and claims are manual, and every payer does it slightly differently.”
We build the payer layer the same way we build the EHR layer: a canonical model for eligibility, authorization, and claim status, X12 270/271 and 276/277 transactions handled through your clearinghouse, per-payer rules captured as configuration, and exception queues for the responses that need a person. Staff stop re-keying and start reviewing.
How this industry actually runs
The operation as we usually find it.
Digital health companies carry an unusual shape: a small engineering team, clinical advisors, a compliance lead who is often part-time, and a sales cycle that stalls not on the product but on a security questionnaire and an interface project scheduled by someone else's IT department. Deployment windows belong to the customer. Integration varies site by site even against the same vendor, and legacy HL7 v2 feeds through an integration engine remain the reality far more often than a clean FHIR API. On the payer side, eligibility and claims run on X12 transactions, prior authorization still involves faxes and PDFs, and operations teams absorb that by hand.
Product, integrations, and the AI feature behind them
Components:
- Your product (web, mobile, API)
- Backend services (queues, jobs, evals)
- AI feature (retrieval, review gates)
- Data & integrations (warehouse, third parties)
Connections:
- Your product to Backend services (API)
- Backend services to AI feature (structured calls)
- Backend services to Data & integrations
What we build
Starting projects that fit Health Tech & Digital Health.
- HL7 v2 and FHIR integration layers with a canonical model and per-site adapters
- Intake, referral, and scheduling systems with constraint-based assignment and waitlist backfill
- Prior-authorization and document automation with extraction, confidence scoring, and human review
- HIPAA-aware engineering: PHI minimization, encryption, least-privilege access, immutable audit logs
- Interface conformance harnesses driven by synthetic data for pre-go-live validation
- Data pipelines for operational reporting, quality measures, and de-identified analytics
- Cloud architecture with environment separation, key management, and enforced retention
- Payer integration: X12 eligibility and claim status transactions via clearinghouse, with per-payer rules and exception queues
Capabilities we bring
Working in Health Tech & Digital Health?
Tell us the line.
What runs by hand, what is not connected, what you are trying to build. An engineer replies within one business day with whether and how we would approach it.
Common questions
What Health Tech & Digital Health teams ask first.
Is Willowark HIPAA certified?
No, and neither is any vendor — HIPAA has no certification regime. Compliance is a property of your organization, your policies, and your agreements with the parties handling protected health information. What we provide is HIPAA-aware engineering: systems built to the technical safeguards, with architecture documented so your compliance team can defend it.
Have you built software for a healthcare provider?
We want to be precise here. Our published work in this space is not clinical. The closest parallel is the AI operating software we built for Jaguar Land Rover's training organization, which removed manual scheduling and logistics work across a distributed set of connected platforms. The transferable part is the engineering, not healthcare domain history we do not have.
Can you work with our customers' EHR interface teams?
Yes, and that coordination is usually the schedule driver rather than the code. We work to their message specifications, test against their non-production environment with synthetic data, produce the interface documentation their analysts expect, and fit into their change windows. Site-specific differences stay in configuration and adapters.
Will you sign a business associate agreement?
Typically, yes — when the work requires us to handle protected health information, which we try to avoid needing in the first place. Most engineering can happen against synthetic and de-identified data in your non-production environments. Where PHI access is unavoidable, we sign your BAA, work under your identity provider and access controls, and keep nothing on systems you do not administer. Your compliance lead sets the terms; we build and operate within them.
Can we use AI on clinical documents without it making clinical decisions?
That is the only way we build it. AI in these workflows typically does transcription-class work: extracting fields from faxed referrals, classifying incoming documents, drafting prior-authorization packets from the chart, and summarizing for a reviewer. Every output carries a confidence score and a link to its source, low-confidence items route to a queue, and a person approves anything that reaches a patient record or a payer. Clinical judgment stays with clinicians, and the audit log shows exactly what the model saw and produced.
Strategy. Software. Systems.
Engineering for Health Tech & Digital Health.
Describe the problem in your own words. An engineer reads it — not a sales script — and tells you plainly what it would take.