Read the wound.
Speak the right language.
WoundHelp AI interprets a wound description with clinical-grade logic, then answers as a patient educator, a caregiver's checklist, a nurse's chart note, or a physician's SOAP note — depending on who's asking.
One engine, five conversations
Same intake, same clinical logic underneath — the response changes with who's asking. Pick a role.
A structured wound taxonomy, not a guess
Sixteen wound categories, color-coded by clinical origin, each tied to staging logic underneath.
Products matched to the clinical picture
Not a one-size list — dressing categories are paired against the specifics of the wound.
Coding and charting, handled in the same pass
Built for clinicians and skilled caregivers who have to make the chart match the care.
Diagnostic mapping
- Wound-category mappings
- Wound-stage logic
- Pressure, diabetic, venous & arterial coding
Procedure coding
- Wound assessment coding
- Debridement coding
- Dressing-change coding
- Evaluation & management concepts
Supply coding
- Dressing category codes
- Foam & alginate products
- Tapes & fixation products
- Reimbursement-aligned classification
Physicians are asked whether to proceed under the SOAP protocol before diagnostic workflows begin — structured assessment, ICD-10 suggestions, CPT/HCPCS guidance, and a treatment pathway in one session.
Training built like clinical education, not onboarding
The same engine runs a modular learning system for everyone who touches a wound.
Structured modules, review sections, and comprehensive testing — with mastery scoring that prevents shallow completion.
Where WoundHelp AI is going
Everything above is live, beta-stage functionality. Here's the build order ahead of it.
Descriptive assessment
Guided conversation, comparative matching, role-adaptive output.
Computer vision imaging
Photograph the wound directly; the model reads type, stage, and tissue condition from the image.
Native EMR integration
Assessments and coding flow straight into the chart, inside the systems care teams already use.
Global deployment
Multi-language, multi-region rollout for care teams worldwide.