DERMIA SOLUTION
DermIA provides an integrated suite of AI-powered dermatology tools designed for screening, triage and clinical decision support.
Core Capabilities
- Skin Image Classification
Identification of suspicious lesions in clinical and dermatoscopic images. - Skin Analysis & Risk Scoring
Automated extraction of visual biomarkers and clinical indicators. - Detection
Localisation of relevant regions of interest for serendipitous findings. - Segmentation
Precise lesion contouring to support monitoring and follow-up.
Designed for multiple users
DermIA is built for:
- Patients – screening, prevention, periodic self-check
- Dermatologists – decision support and workflow optimisation
- Clinics & Healthcare Institutions – scalable triage solutions
- Medical software & device manufacturers – integration of AI engines
- Organizations requiring custom AI models – tailored development for specific needs
Regulatory Status
DermIA is ready for deployment but not yet certified.
We are working towards CE certification as a SaMD.
TECHNOLOGY
DermIA’s technology is based on proprietary deep learning pipelines developed through years of academic and clinical research.
Key Components
- Proprietary Deep Learning Models
Designed specifically for dermatological imaging and optimised for real-world variability. - Clinical-grade Datasets
Models trained on curated datasets validated by dermatologists. - Multi-modal Integration
Combining images with metadata (age, sex, anatomical location, clinical notes) for more robust predictions.
Flexible deployment
Our technology can be integrated into:
- Digital platforms (web, cloud, mobile apps)
- Physical systems and medical devices, including local offline inference without internet connectivity
- Embedded modules suitable for edge-AI hardware
This makes DermIA scalable, adaptable and ready for cross-sector applications.
CUSTOM AI SOLUTIONS
Our research team develops custom AI systems for organizations with unique challenges.
We offer:
- bespoke dataset preparation and annotation
- tailored model development
- optimization for edge or cloud deployment
- integration into existing digital or hardware systems
