Smart Entrepreneurial Assessment System (SEAS) – SEAS CONTINUATION PROJECT

Term: 
2023-2024 Summer
Faculty Department of Project Supervisor: 
School of Management
Number of Students: 
4

This project aims to develop an advanced smart system that will enable Venture Capital (VC) and other investment entities to rapidly and comprehensively analyze implementation, psychological and behavioral analysis, and a precise evaluation formula to enhance the evaluation process, providing a reliable tool for swift decision-making in the investment landscape.
From an academic perspective, the project explores the interdisciplinary nature of entrepreneurial success by combining data science, artificial intelligence, and behavioral analysis. This holistic approach ensures a nuanced understanding of the multifaceted factors contributing to startup success. The project's ultimate goal is to develop a smart assessment system that will enable investors to make more informed decisions in the dynamic and competitive startup ecosystem.
The project focuses on developing an advanced smart system for the rapid and comprehensive analysis of entrepreneurial ideas and teams, catering to Venture Capital and other investment entities. The initiative involves data analysis, AI implementation, psychological and behavioral analysis, and the creation of a precise evaluation formula.
By integrating these components, our system will enhance the evaluation process, providing a reliable tool for swift decision-making in the investment landscape. From an academic perspective, the project addresses the interdisciplinary nature of entrepreneurial success, combining data science, artificial intelligence, and behavioral analysis. This holistic approach ensures a nuanced understanding of the multifaceted factors contributing to startups' triumph. Our smart evaluation system will ultimately contribute to more informed investment decisions in the dynamic and competitive startup ecosystem.

Related Areas of Project: 
Computer Science and Engineering
Industrial Engineering
Management