Startup Investment Suggestion System Using ML

ABSTRACT - For a failing company, investment techniques are a sure-fire way to get the returns they need. For businesses in the early stages of their development, such as startups, the anticipated execution of the plan is still a challenge. This is a problematic scenario since it could lead to many mistakes in achieving the investment potential, which could have devastating consequences. A prospective investor may lose out on a great chance to put money into a ground-breaking business, which can make the problem much worse. Seed financing is crucial for startups to reach their goals. That was also the moment when investors started putting a lot of money into the business, which would be crucial for its future growth. Indeed, there is a dearth of relevant literature on the methods for providing investors with thorough and accurate investment suggestions. To that end, we have developed an interactive software that makes use of K-Nearest Neighbors and Decision Making to provide recommendations for investments. Investors and companies using this platform have benefited from the proposals' ability to bring their ideas to fruition. The provided approach has produced quite satisfactory results, so the findings must be good. Keywords: Investment Opportunity, K-Nearest Neighbors, and Decision Making.