Yes I will vouch the same, I worked on same prototype, by spending around a hundred bucks to generate meaningful knowledge graph before hand. The right chunking of text, with embeddings will auto cluster content in vector db. Knowledge graph is later part,tbf redundant.
this is a really bad take. for li, amazon etc. the relationships are well defined and known before constructing the graph. but if it comes to 'memory' for agents you don't want to rely on a graph since relations are unknown beforehand, keeping it up to date is a pain if the relations are semantic, ah and if you use an llm to build the graph you will suffer from models producing different relations for the same thing. don't use graphs, just give the models a really good searchView quoted post on X
