Gensim is great for generating certain types of embeddings, but not for operationalizing them. It doesn’t do approximate nearest neighbor lookup which is a deal breaker for most models that use embeddings at scale. It also do not manage versioning so you end up having to hack a workflow around it to manage embedding. Finally, it’s not really data infrastructure like this is, so you end up doing hacky things like copying all your embeddings to every docker file. With regards to serving embeddings, gensim is just a library that supports in-memory brute force nearest neighbour look ups.