Abstract:

This paper presents the concept of an agent-based, distributed web application utilizing artificial intelligence (AI) for forecasting startup profitability. The proposed system integrates key success factors (KSFs) to evaluate financial and operational performance across different stages of a startup’s life cycle. The application employs autonomous agents that collect, process, and analyze multidimensional data to generate profitability forecasts and recommendations. The multi-agent architecture ensures scalability, adaptability, and resilience through asynchronous communication and self-organizing behaviours. Seven types of agents are defined performing specialized tasks to enable collaborative learning and dynamic decision-making. The system design allows further extensibility by adding new agents. This concept provides a foundation for the development of intelligent decision-support tools that assist entrepreneurs and investors in making data-driven strategic choices throughout a startup’s lifecycle.