Early Stage Startup

Early-stage startup research focuses on predicting startup success and optimizing the product development process. Current efforts leverage machine learning, particularly deep learning models and large language models (LLMs), to analyze diverse data sources like Crunchbase profiles and founder characteristics to improve prediction accuracy. These models are being applied to predict various success metrics, from securing funding to achieving an IPO, and to enhance requirements elicitation during product development. This research offers valuable tools for investors and entrepreneurs alike, improving investment decisions and streamlining the often-challenging early stages of a startup's lifecycle.