Instant Dermatology Review
Skin concerns reviewed within minutes by AI and confirmed by a dermatologist, instead of waiting weeks for a referral.
- For
- Public health district officers in Southeast Asia or East Africa
- Solves
- Rural clinics lack specialist access and face long referral queues that delay treatment.
- Delivers
- Structured differential diagnosis, biopsy code, treatment plan, prescription suggestions, billing code
- Built in
- about 6 weeks of creation time, MVP in 7 days
- Investment
- $11,500 for the MVP, $46,500 for the full product
- Run it
- Inside your business, or as part of your offer to clients
What it does
For public health district officers, turn clinical images and patient history into a specialist diagnosis and treatment plan.
- Secure image upload and history entry.
- AI vision model analysis of dermoscopic images.
- AI language agent drafting differential diagnosis.
- Specialist review and editing of AI draft.
- Automated report generation with codes and treatment plans.
- Integration with billing and patient records.
What goes in, what comes out
- Clinical images
- Patient history
AI drafts, people review. Evidence-backed analysis and reporting workspace.
- Structured differential diagnosis
- Biopsy code
- Treatment plan
- Prescription suggestions
- Billing code
How it works
The workflow
- InStart with
Clinical images and patient history
- 1
Nurse uploads clinical image and enters patient history
- 2
Vision model analyses the dermoscopic image
- 3
Language agent drafts a provisional differential diagnosis
- 4
Specialist reviews the AI draft on a mobile dashboard
- 5
Specialist edits the draft and approves the report
- 6
System generates the final structured report
- 7
Report is delivered to the clinic for immediate treatment
- OutFinish with
Structured differential diagnosis, biopsy code, treatment plan, prescription suggestions, billing code
AI does the heavy lifting, people stay in charge
A vision model trained on dermatology datasets analyses the image and a language agent drafts a structured differential diagnosis. A human specialist reviews the draft for accuracy and signs off on the final report.
What your team sees
Key screens: Image upload portal, specialist review dashboard, report delivery interface. Use a secure upload portal for the nurse, a mobile dashboard for the specialist, and a report viewer for the clinic. The specialist can edit the AI draft on their phone. The nurse receives the final report immediately.
Accounts and administration
User roles for nurses and specialists, audit trails for all reviews, version control for reports, access permissions based on clinic location
Integrations and data access
Hospital records systems, billing systems, WhatsApp API
How we build it
We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.
- 1
Scoping call
Day 1Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.
- 2
MVP
7 daysOne buyer segment, one recurring use case. Manual review in the loop. Built by our AI software factory.
- 3
Paid pilot
8 daysAccounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.
- 4
Full product
3 weeksSelf-serve onboarding, billing, monitoring and the wider integration set.
- 5
Run and improve
MonthlyWe host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.
Why we start with an MVP
An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.
- Pick the riskiest assumption. Here: will public health district officers in Southeast Asia or East Africa use it to solve "rural clinics lack specialist access and face long referral queues that delay treatment"?
- Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
- Run a paid pilot. Prove that diagnosis accuracy matches specialists and turnaround time drops from weeks to minutes.
- Measure, then decide. Track diagnosis accuracy rate and turnaround time reduction. Then expand, change course or stop, with evidence instead of opinions.
MVP scope for this solution. One clinical pathway for skin lesions, five volunteer specialists in one city, WhatsApp submission endpoint
After the MVP. Automated triage for other conditions, mobile app for nurses, broader specialist network
What the build depends on. High quality dermatology datasets, specialist availability
Investment
A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.
- Phase 1
MVP
One buyer segment, one recurring use case. Manual review in the loop.
- Phase 2
Paid pilot
Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.
- Phase 3
Full product
Self-serve onboarding, billing, monitoring and the wider integration set.
Indicative total, MVP to full product$46,500about 6 weeks of creation time · start with the MVP from $11,500
Running costs per month
A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.
| Stage | Hosting and infrastructure | AI usage | Total per month |
|---|---|---|---|
| MVP and paid pilotabout 3 customers | $50–$100 | $80–$160 | $130–$260 |
| Full productabout 50 customers | $190–$380 | $880–$1,750 | $1,070–$2,130 |
Run it or resell it
For your own team
Public health district officers in Southeast Asia or East Africa run it inside the business: clinical images and patient history in, structured differential diagnosis, biopsy code, treatment plan, prescription suggestions, billing code out, reviewed by your people.
As part of your offer
Agencies, consultancies and software companies can offer it to their own clients under their brand. We build and maintain it; you sell and deliver it.
Your brand, or this one
Run it under your own brand, or start from this concept style.
- primary
#379127 - accent
#9554c9 - surface
#e6f1e4 - ink
#22201e
- Headings
- Libre Baskerville
- Text
- IBM Plex Sans
- Voice
- Careful, kind, clinically plain
Selling it to your own clients: the go-to-market playbook
Pricing to test
Flat annual license per clinic plus a fee per specialist review
Message to test
Get a specialist opinion in minutes not weeks
Where to find buyers
Public health networks, medical associations
Lead magnet
Free demonstration for one clinic
The first 30 days
- Week 1: Train vision classifier on open datasets.
- Week 2: Build review queue for five specialists.
- Week 3: Launch WhatsApp endpoint.
- Week 4: Gather feedback and refine.
Paid pilot
Prove that diagnosis accuracy matches specialists and turnaround time drops from weeks to minutes.
Success metrics
Diagnosis accuracy rate, turnaround time reduction
Retention and expansion
Annual contracts, network effects
Why clients would pick it
High quality dermatology dataset, established specialist network, liability protocols
Alternatives and positioning
Referral to central hospital which takes weeks, travel to capital city which is expensive, telemedicine which requires specialist availability
Main delivery costs
Specialist network management, server infrastructure, data storage
Safeguards
Scope restriction to one condition at a time, disclaimer that report is a decision aid, mandatory human sign-off