Hi everyone, this is my second post on my blog. I am currently working on InvestorMatch.ai project, which aims to create a tool that scores the relationship between potential funders and potential founders and finds the best funder matches for the founders and the best founder matches for the funders. I want to write about my favorite technology we are using in our project.
One of the technologies we are using for the project is Weaviate vector database, which helps the users to match criteria of the funders and the founders using semantic search, instead of text search. This way, the search results in a rate between a minimum and a maximum (such as 0 and 1) where the maximum corresponds to strongly similar, and the minimum to least similar, depending on the meaning of the criteria based on a certain context. The similarities are found based on some vectorization models. The best part I like with this database is that the users can choose any vectorization model they want that is available in the market, or they may prefer to develop the model themselves.
On the other hand, I believe the database could be made better if there was a built-in user-friendly GUI for the database. This would help beginners to follow their actions on the database easier.
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