Sycai Technologies is a technological start-up founded in Barcelona in 2020, born from the motivation of empowering radiologists to improve healthcare through artificial vision and big data. We develop AI-based algorithms, which helps medical professionals in the diagnosis of abdominal injuries and in the prediction of their evolution to increase early-stage cancer detection and improving the quality of life of patients with chronic diseases. During the COVID-19 pandemic, we decided to apply our technology to help medical professionals to fight against Coronavirus, so we developed AI MedAssist.
Working in a medical environment made us realize how such products can support gastroenterologists and specialists in radiology in their daily routine.
Photo: Ainhoa Gomà
We are sure that medicine and technology working hand to hand will revolution diagnosis activities and patient care how we know it.
Faster, simpler and more accurate diagnosis will improve the life quality of people with chronic diseases, speeding up the process and avoiding unnecesary tests.
Thanks to AI-based algorithms, optical biopsies are a new reality, that allows doctors to detect the presence of malignant forms with non-invasive methods, even before they have appeared.
We want to help doctors increasing the detection of early stage cancer for the whole abdomen and optimizing the follow up protocols for chronic patients.
Photo: Ainhoa Gomà
Chief Executive Officer
Mechanical engineer at Politechnical university of Madrid and MsC at Technical university of Munich. Three patents published. Working experience managing talent and innovative projects. Currently finishing a MBA
Chief Technical Officer
Robotics engineer at Politechnical university of Madrid and MsC at Technical university of Munich. Currently finishing a PhD in Deep Learning at Politechnical University of Catalonia. Lecturer and researcher
Gastroenterologists. Consultant at University Hospital Doce de Octubre Madrid. Training in advanced endoscopy techniques and clinical research at Instituto Portugues Oncología