Pipralab

The Story Behind SkinX

Inspiration

Skin cancer and other skin conditions often go unnoticed because people lack access to affordable dermatological guidance and may not recognize early warning signs. We wanted to explore how artificial intelligence could help bridge this gap.

That idea led to SkinX — an AI-powered dermatology triage platform designed to make preliminary skin health assessment and reliable medical information more accessible.

What We Built

SkinX combines multiple AI technologies into one platform:

• AI Skin Lesion Classification: Deep learning models analyze uploaded skin images to identify potential skin lesion categories.
• Image Segmentation: Computer vision techniques help identify and isolate relevant lesion regions.
• AI Dermatology Assistant: A Retrieval-Augmented Generation (RAG) system provides context-aware responses grounded in dermatological knowledge.
• Accessible Platform: A web-based interface allows users to upload images, explore preliminary assessments, and access educational guidance.

How We Built It

We developed SkinX using a combination of deep learning, computer vision, backend APIs, and modern web technologies. Our architecture integrates image-processing models with an AI-powered medical knowledge retrieval system.

We also focused on deployment, API integration, secure image handling, and making the system accessible through a production-oriented infrastructure.

Challenges We Faced

Building SkinX involved several challenges:

• Integrating image classification and segmentation into a unified workflow.
• Reducing unreliable AI responses through domain-specific RAG retrieval.
• Handling image uploads, model inference, and backend communication efficiently.
• Deploying and maintaining multiple interconnected services.
• Balancing AI capabilities with responsible medical communication.

What We Learned

This project taught us that building an AI healthcare solution requires more than model accuracy. Reliable knowledge retrieval, responsible communication, system integration, and accessibility are equally important.

Our Vision

We envision a future where AI helps people become more aware of their skin health and recognize potential warning signs earlier. SkinX is a step toward making dermatological guidance more accessible, with the goal of supporting—not replacing—professional medical evaluation.## Inspiration

What it does

How we built it

Challenges we ran into

Accomplishments that we're proud of

What we learned

What's next for Pipralab

Built With

• artificial-intelligence
• cloud
• computer-vision
• deep-learning
• docker
• fastapi
• image-classification
• image-segmentation
• javascript
• linux
• llm
• machine-learning
• medical-ai
• natural-language-processing
• python
• pytorch
• rag
• react
• rest-api
• vector-database