Healthcare AI Consulting & Development, from Use-Case Scoring to Governed Production

Yes, with the right setup. We use HIPAA-eligible model services covered by a business associate agreement, configured so your data is not used to train the vendor's models, send only the minimum data each task needs, de-identify where possible and log every prompt and response. Where a cloud model is not acceptable, we deploy open-weight models in your own environment.

It depends on what it does. FDA's clinical decision support guidance, updated in January 2026, excludes many tools that support a clinician who can review the basis for the recommendation; software that analyzes medical images or signals, or drives treatment on its own, is usually a device. We map each feature against the guidance and build device software with design controls and a predetermined change control plan, but the regulatory decision and any submission sit with you and your regulatory counsel.

ONC's HTI-1 rule requires certified health IT to support source-attribute information for decision support interventions, including 31 attributes for predictive tools covering training data, validation, performance and fairness. The HTI-5 proposal published in December 2025 would remove much of this "model card" requirement, but it was not final at the time of writing. We build transparency information into every decision support tool either way, because buyers and AI committees ask for it.

Several. California requires disclosure when generative AI is used in patient communications, Texas requires providers to disclose AI use in care, Illinois bars AI from acting as a therapist, and a growing number of states require a human to make coverage denials. Colorado replaced its broad AI Act in 2026 with a narrower notice-based law that takes effect in January 2027. A December 2025 executive order challenges state AI laws, but they stay in force unless a court or Congress says otherwise. We map the rules for the states you operate in.

Agents get only the permissions their task needs, work from approved tools, pause for human approval before any action that reaches a patient, payer or record, and log every step. We test them against failure cases and prompt-injection attacks before release and monitor them afterward.

We build a test set from your own data, measure accuracy against clinician-reviewed answers, report performance by age, sex, race and ethnicity, payer and site where the data allows, and document known limitations. The same tests run again after every model, prompt or data change.

Start with retrieval-augmented generation (RAG) for most knowledge tasks: answers come from your current guidelines, protocols and policies, with the source cited, and updating knowledge means updating documents. Fine-tuning helps when you need a specific style, format or specialty vocabulary that prompting and RAG cannot deliver. Many systems use both.

A scored list of use cases, a readiness report covering data, EHR access, infrastructure, skills and governance, a build-or-buy view for the top candidates, the risks and regulatory questions for each, and a costed, sequenced roadmap.

Yes. We build workflows that check whether authorization is needed, gather the documentation from the chart, assemble the request and track status, using the Da Vinci CRD, DTR and PAS standards behind the CMS prior-authorization API requirements due January 2027. For payers, a clinician makes every adverse decision.

We agree the baseline and the target metric before the proof of value, such as documentation time, coding turnaround, denial rate or authorization cycle time, then measure the same metric in the pilot and after launch, alongside model and hosting costs.

We monitor accuracy, drift, hallucination, bias and cost in production, alert a named owner when thresholds are crossed, retrain or roll back as needed, and apply regulatory changes as they arrive. You can keep us on support, move to a dedicated team or take the system in-house.

You do. Every model, prompt, evaluation set, pipeline and line of code we build for you is yours, documented so your team or another partner can run it.

We combine 16+ years in healthcare, 100+ healthcare projects and dedicated HL7, FHIR and DICOM practices with an AI team that builds what it recommends. Add CMMI Level 3 and ISO 27001 delivery, a US team in Bloomington, Minnesota and full ownership for you, and you get advice you can act on and a system you can defend. Button: View All FAQs