Mindbowser built an AI-native Intelligent Health Record for precision and longevity medicine practitioners. It covers the full care journey: intake, pre-visit preparation, real-time ambient documentation, post-visit automation, and patient engagement.
Talk to Our TeamFunctional and longevity medicine practitioners managing biomarker trends and multidisciplinary care
Full platform build, from patient intake through post-visit automation
AI ambient scribe, real-time NLP, LLM document processing, bi-directional EMR/EHR integration
The gains came from removing manual steps before, during, and after the visit.
reduction in provider documentation time through real-time AI transcription and automated SOAP note generation
reduction in post-visit follow-up time with automated lab orders, referrals, and treatment plan updates
increase in patient interaction through an AI inbound assistant handling scheduling, reminders, and patient inquiries
improvement in care coordination through AI-driven automation across multidisciplinary workflows
A 2023 MGMA report found specialty practices spend an average of three or more hours per provider per day on EHR documentation. Functional medicine charting runs longer, because every encounter carries longitudinal biomarker panels and multi-visit histories.
Providers transcribed conversations into structured SOAP notes after each visit, adding hours of administrative work on top of clinical care.
PDFs, handwritten notes, and scanned lab reports sat in every practice. Turning them into treatment plans and patient communication took manual review at each step.
Prescriptions, lab orders, referrals, and scheduling were handled by hand. In high-volume practices, backlogs built up and care quality slipped.
Bi-directional exchange across EMR and EHR platforms was complex and unreliable. Booking, follow-ups, and routine inquiries ran through staff, capping how many patients a practice could engage without adding headcount.
Discipline-specific intake forms feed automated document tagging and upload. Patient data syncs to connected EMR and EHR systems in real time, and AI validation flags missing or inconsistent data before the visit begins.
Before each visit, the platform turns patient data into a structured summary. In multidisciplinary clinics, each clinician sees the data relevant to their specialty without filtering through the full patient record.
The scribe transcribes the patient-provider conversation as it happens and generates SOAP-format notes during the visit. The first model handled general vocabulary well but lost accuracy on biomarker panel names, specialty lab protocols, and supplement nomenclature. We rebuilt the post-processing layer with a domain-specific vocabulary extension before the scribe reached production.
Post-visit work that providers and staff used to do by hand now runs automatically. Patients get a portal for everything that follows the visit.
A patient-facing assistant handles booking, follow-ups, and inquiries over chat and voice. Intent classification separates informational questions, which the assistant answers, from clinical ones, which route to a clinical workflow.
Talk to us about what an AI-native clinical workflow looks like for your team.
Partner with us to design, build, and scale digital solutions that drive better outcomes.
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