Self-hosted search
Search that decides relevance by holding an election.
OpenBeam is open-source search across everything your team already uses. It reads your tools, and when you ask it something, it does not trust any single way of finding the answer.
The idea it taught me
A search for "q3 pricing deck" is three questions at once. There may be a file named exactly that, which rewards matching the words. The right document might be called "autumn revenue review" and never say deck, which rewards matching the meaning. And "q3" carries more weight than its three letters suggest, which rewards a model that has learned which rare words matter.
OpenBeam answers all three separately, then holds an election. Each retriever ranks the documents its own way, and instead of trying to add up scores that live on different scales, it keeps only the ranks and lets them vote. A document no single retriever loved but all three liked can win, which is usually the right call.