A.I. VALI uses proprietary Machine Learning (ML) and Deep Learning (DL) techniques to analyze the data collected from medical images, such as tissue biopsies and endoscopies.
Our modular A.I. tools empower our clients with accurate, reproducible, and affordable platforms at a global level. These platforms have a critical impact on the early detection of cancer in order to provide the best-personalized treatment model for each patient.
A.I. VALI offers services in research and development, analytical validation, optimization, and validation for regulatory submissions. These services can be utilized by our clients and incorporated into the early stages of drug development through clinical trials and validation of biomarkers, or companion diagnostics (CDx), by providing a precise interpretation of information on cell functioning, as well as the structure of critical proteins and biomarkers.
Our extensible data science environment and toolkit were built to serve as an architectural framework and community platform for developing and distributing reusable data visualization modules and reusable multi-modality data integration pipelines. Our innovative system allows our team to develop the algorithms, validate them properly, and either commercialize them directly or support our clients in their efforts to commercialize these products.
We are eager to collaborate with researchers and clinical scientists in all medical imaging fields. If you are interested in learning more about how A.I. VALI can help develop or provide a solution for your project, please get in touch with us!
Vision & Mission:
The vision of A.I. VALI is to utilize artificial intelligence platforms in the analysis of medical images. These platforms will be used for research and development of new, innovative therapeutic models by pharmaceuticals and biotech industries, and for clinical use in hospitals under a regulatory compliance environment.
The mission of A.I. VALI is to collaborate with academic, clinical, pharmaceutical and biotech industry partners, in order to leverage existing resources, support innovative research projects, and empower each with A.I. platforms for the early detection of cancer and the development of personalized treatment models.