hey @scroobiustrip, have you tried first passing the embeddings through UMAP before applying a density based clustering algorithm? there’s a nice discussion on this approach in the UMAP docs 15 which comes with the following warning:

This is somewhat controversial, and should be attempted with care. For a good discussion of some of the issues involved in this, please see the various answers in this stackoverflow thread 9 on clustering the results of t-SNE. Many of the points of concern raised there are salient for clustering the results of UMAP. The most notable is that UMAP, like t-SNE, does not completely preserve density. UMAP, like t-SNE, can also create false tears in clusters, resulting in a finer clustering than is necessarily present in the data.

the example in the docs actually seems to exhibit some of the problems you found with e.g. HDBSCAN in your application