There are tons of algorithms from academia like DBSCAN, BFGS and so on that are fairly complex to implement by yourself. It would take days to translate papers

There are tons of algorithms from academia like DBSCAN, BFGS and so on that are fairly complex to implement by yourself. It would take days to translate papers on these subjects to get usable algorithms - if you have enough background and skills, of course. Even then you would miss out on all the improvements that subsequent papers have brought out. In nutshell, to get to the state of art for cutting edge algorithms is extremely time and skills incentive. This website can solve this huge problem. I think, as a startup, you might want to cut down on "making money" part and especially muddy waters of patents. These are likely not the greatest incentives either for researchers or consumers given that lot of grants don't allow this and even if it did many researchers settled in academia have severe repulsion to it. Instead try to grow the site organically keeping it as frictionless as possible for both sides of users. Motivate researchers to post code and data, for example, to allow them compete against state of the art. Be the that reputed site for computational problems and algorithms that people go to like they go to Stackoverflow for programming problems. Once you establish yourself like that, researchers want to get benchmark from you to cite in their papers and that's great motivation for them to give you their code. Consumers can then find them in your repository. I would suggest to keep making money as TBD. Just grow the site making it largest possible index of computational problems and known state of the art solutions.