Better healthcare,across the board.
One AI engine that reads the note and the image. Two applications: complete billing for U.S. dermatology, diagnostic support for clinicians where a dermatologist is not available.
Live today with Schweiger Dermatology Group. Integrated with ModMed EMA.
One engine, two answers.
- The noteHistory and documented complexity
- The imageThe clinical photograph
- The visitWhat happened in the room
- Insight MDMissed codes surfacedU.S. dermatology, before the claim
- Assist MDRanked differentialIndia, where there is no dermatologist
The provider in the room is carrying more than ever.
The expertise is scarce. The work has shifted. The revenue is leaking. None of those gaps can be hired away.
outpatient visits under-coded
National coding audits, 33 to 45%
dermatology claims denied on first submission, about double many specialties
Industry claims data
spread in biopsy rates between newer and senior providers
Analysis by provider experience
projected U.S. physician shortfall by 2036
AAMC
The engine
AI that reads the visit, the note and the image together.
Illustrative. Lesions ranked for clinician review. Rings and ranks are examples, not model output.
Hundreds of thousands of pathology-confirmed images. The set grows with every biopsy result that comes back.
Assembled before the engine was built. In AI, that head start is unusual.
The India work adds depth in the darker skin types where published models perform worst.
The provider reviews it and decides, every time.
Two applications of one engine, in two markets
Insight MDUnited StatesThe revenue you already earned, before the claim is built.
For U.S. dermatology groups. Insight MD reads the history and the visit, weighs complexity, and surfaces the codes a ten-minute visit routinely leaves behind. It runs inside the EMR you already use, before billing.
- Under- and over-coding caught before the bill
- Every encounter checked for missed codes, before the claim
- Every code with a defensible basis
- Live today at Schweiger Dermatology Group, in ModMed EMA
Codes surfaced on one encounter
Revenue audit
How much is your practice leaving on the table?
Send a year of de-identified claims. We come back with the codes your group is missing and what they are worth, code by code.
Assist MDGlobalWhere there is no dermatologist, a ranked differential.
Currently being used by primary-care clinicians in India, delivered with NGOs and state health partners. Assist MD reads the clinical image and the history together and returns a ranked differential with next steps, over the low-bandwidth connections rural clinics actually have.
- 70+ conditions, about 90% of presentations seen in practice
- Deepest where general models degrade: Fitzpatrick IV to VI
- Built to run over low-bandwidth rural connections
- Provider-directed by design
Illustrative case. Basis shown for each row; next step surfaced in the workflow. The clinician decides.
Assist MD · the market
The expertise isn’t where the patients are.
India has roughly one dermatologist per 100,000 people, most of them in cities, while seven in ten people live in rural areas. Skin disease is among the top five reasons for an outpatient visit. Assist MD is in clinical validation at RIMS Ranchi, and is built to sit inside India’s national telemedicine platform when validation completes.
dermatologists in India
the rural-to-urban gap in dermatologist density
National dermatologist density data: about 1.9 per million rural, 23.4 per million urban.
Built by a dermatologist who spent eleven years in the exam room.
Dr. Kautilya Shaurya practiced in New York for eleven years and directs the APP Program at Schweiger Dermatology Group. HealthyMe AI is what he built after working inside those gaps every day. Third-generation physician. Roots in Ranchi.
Two-year commercial contract. 2.4M annual visits. Scope expanding in year two. Dr. Shaurya directs the APP Program there. Integrated with ModMed EMA.
How Insight MD works
It runs inside the EMR. Live today in ModMed EMA.
FHIR integration, live today in ModMed EMA. No new screen for the provider.
The engine reads the note and the image as the visit happens.
The provider sees the differential and the codes, reviews the basis, and makes the call.
What we commit to.
The audit
One code left $5M a year on the table. There are thousands of codes.
encounters analyzed
qualified for G2211
billed
identified per year, this code alone
Three audited patterns at one group: more than $11M a year identified.
Full-year G2211 audit at Schweiger Dermatology Group, as of August 2026. 46% sits inside CMS’s own 38 to 54% projection for the code. Assumes a 41.8% net collection rate and $5 net per encounter. First recovery readout is next.
Ask us the questions you need to ask.
Whether someone sent you here or you found us, the next step is the same. Write to us and we’ll set up a call.
Send a year of de-identified claims and we come back with what your group is leaving on the table, code by code.
A clinical decision support tool. It surfaces findings and a ranked differential for the clinician to review, with the basis for each. The clinician makes every diagnosis and every treatment decision.
The gaps have a price.We measured it.
For patients: Stage I melanoma treated after 120 days carries 41% higher mortality.
For practices: one in three outpatient visits is under-coded, as much as $100K a year per provider. About 14% of dermatology claims are denied on first submission, and roughly 90% of those denials are preventable.
Sources: published melanoma outcomes by time to treatment; national coding audits; dermatology claims analyses. Citations available on request.
Live in the U.S.In validation in India.Ophthalmology next.
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