BulletProve is responsible for the development and implementation of AI algorithms for video analysis and motion pattern detection in infants, in accordance with the Prechtl General Movements Assessment method.

- Computer Vision and Machine Learning applied to infant movement analysis from video recordings
- Development of training pipelines and neural network architectures
- Detection and segmentation of pathological movement patterns
- Integration of AI algorithms with clinical neurological assessment systems
- Close cooperation with medical teams responsible for data evaluation and model validation

AI-driven project supporting early and non-invasive detection of endometriosis. BulletProve develops advanced diagnostic tools that analyze multimodal medical data to identify patterns associated with the disease.

- Design and implementation of AI and Machine Learning algorithms for medical data analysis
- Analysis of imaging data such as MRI and ultrasound (USG)
- Development of predictive models supporting differential diagnosis
- Processing of non-invasive data sources, including imaging and patient-reported symptoms
- Strict compliance with GDPR and high standards of data anonymization
- Collaboration with clinical partners for dataset creation and real-world validation