Aimazing is a B2B medical software product delivered as a secure web application. It is designed to be deployed by dermatology clinics as their primary system for AI-augmented patient skin assessments, progress tracking, and report generation.
The platform operates entirely in the cloud, requiring no local software installation. Clinics subscribe on a per-seat or per-clinic basis. All patient data is encrypted, access-controlled, and stored in compliance with established medical data security standards.
Every skin image submitted through the platform passes through a structured AI pipeline that produces structured, reproducible clinical data.
Clinicians photograph the patient's affected skin area using a standard clinical camera or smartphone. The image is uploaded to the platform via a browser-based interface. All uploads are transmitted over TLS and stored in encrypted cloud object storage.
The uploaded image is sent to a deep learning model hosted on Amazon SageMaker. The model identifies and classifies visible skin conditions, estimates severity using a structured scoring system, and segments the affected region within the image.
AI results are returned in a structured JSON format and stored in the patient's clinical record. The clinician reviews the findings, adds clinical notes, and the data is appended to the patient's longitudinal treatment timeline.
Every feature in Aimazing is designed specifically for clinical workflows in dermatology — not repurposed from generic SaaS tooling.
The platform detects over 15 dermatological conditions including acne, eczema, psoriasis, rosacea, and hyperpigmentation using a trained convolutional neural network model.
Compare analysis results across clinic visits using quantitative metrics. The platform generates visual trend lines for each tracked condition, enabling objective outcome measurement.
Generate structured PDF clinical reports in one click. Reports include AI findings, annotated images, clinical notes, progress charts, and treatment recommendations.
Each clinic account includes multiple user roles — clinic administrator, attending dermatologist, and clinical assistant — with access permissions scoped to their function.
All patient data — images, notes, and analysis results — is stored in structured relational records with encryption at rest. Access is enforced by AWS IAM policies.
The entire platform runs in the browser. Clinics do not install any software. Access is managed through secure credentials, making deployment and onboarding straightforward.
| Workflow Step | Without Aimazing | With Aimazing |
|---|---|---|
| Image Storage | Phone camera rolls, USB drives, shared email threads | Encrypted object storage in Amazon S3, linked to patient records |
| Condition Assessment | Visual inspection only, no quantitative scoring | AI-based classification with confidence score and severity index |
| Progress Tracking | Verbal notes, subjective comparison, no baseline | Quantitative trend charts across all recorded clinic visits |
| Report Generation | Manual Word or PDF documents, 20–40 min per report | One-click structured PDF report in under 60 seconds |
| Record Access Control | No enforced access control on shared drives | Role-based access with per-record audit trails |
| Data Security | Varies by clinic; often no formal compliance posture | AES-256 at rest, TLS in transit, AWS IAM-enforced access |
We are accepting pilot clinic applications. Join our early access cohort and help shape the product roadmap.