Soph.AI is the artificial intelligence software which enables universities to detect early dropout signals for their students and help retain them for the benefit of both universities and students.
Soph.AI uses AI/ML models built on big data to learn and improve prediction capabilities for each specific faculty/university, making it extremely relevant for each specific institution.
This allows universities to:
Soph.AI uses standardized student socio-economic data provided during faculty enrollment and combines it with student performance over time to determine dropout risk. Socio-economic background plays a critical role in student success and this is why we’re using this as a backbone for our ML model.
The key advantage Soph.AI has in the short run is its level of automation and consistent learning ability based on students’ individual performance through time.
In the long run, we rely on our unique adaptability to each faculty’s characteristics in order to provide a personalized experience.
Our model is built on continuous learning and improving as the model grows (compound value year-on-year), and we’re able to analyze multifactorial environments and trends that contribute to the student dropout problem around the world.
This gives us a much higher and more accurate ability to assess drop out risks and to flag these cases early so that the faculties can react and keep the students engaged and enrolled.
The project is financed by the Innovation Fund from the European Union Pre-Accession Assistance and from the budget of the Republic of Serbia, the line of the Ministry of Science, Technological Development and Innovation.
