We offer a product or service for acquisition tailored to our customer’s needs. To implement real-life use cases, we rely on the domain knowledge and on the test data of our customer. The project initiation can begin after predefining the exit price, acceptance criteria, scope, and KPIs jointly.
E-Group brings the technology excellence, experience, access to the right research-pipeline and infrastructure for development in the DATA, TRUST and XCHANGE product areas.
As an integral part of the Hungarian international academic scene, E-Group has an established scientific network. When collaborating with us, you gain access to qualified data scientists, clinicians, statisticians, mathematicians, and economists as well as industry research labs and top universities.
E-Group discovers the bespoke Machine Learning (ML) algorithms and models that match your specific requirements and enable your company to focus on its strengths.
We utilize our infrastructure and leverage our AI expertise to understand your challenge. After refining and improving the data, we build and train the deep learning model, which we can later integrate into your legacy or state-off-art systems.
E-Group is your best champion in Lab-To-Market (L2M) initiatives funded by the EU Innovation Ecosystems. As the launch customer, you bring your challenge, and we assemble the right group of partners selected from market leaders based on our industry experience to solve it.
We open access to our valuable network of partners, professors, academic talent pools, and labs. Together, we find the right source of funding. E-Group will harmonize the work of the consortium and will be responsible for the overall development of the product or solution.
We are working with excellent Hungarian as well as foreign universities. We are happy to give opportunities for students, PhD students, teachers, professors to work on real products, real problems, and to achieve tangible results together: a real product is born under our hands, a new publication, not just a methodology or a theory. Our common tasks include technological research and design, algorithm development and testing, POC creation and validation and market entry works.
The main aim of the InnoHealth Datalake project (IHDL) is to develop and implement the concept of a novel complex IT system capable of collecting, storing and analyzing all types of health data (which are generated in healthcare activities and services at the University of Pécs, together with all relevant external data). It also serves as a prototype for domestic and regional healthcare systems.
The Datalake’s principal capabilities were identified according to current and future needs of healthcare including data collection (independent of size, type and source of data), data storage and data analyses by state-of-the-art analytical methods and tools supporting healthcare services and R&D&I activities.
