Similarity isn't relevance: the hard part of semantic search

Here's a dirty secret of search: "the closest match" and "the most useful result" are not the same thing. Return the mathematically nearest document and you'll often hand someone something technically related and practically useless. Relevance is a harder problem than similarity — and it's where good search is won or lost. Getting that right was the core challenge in the GovernAI Research Atlas , a semantic discovery platform I built to unify research across papers, repositories, and policy. Similarity is not relevance Semantic search gives you a superpower: embed everything into vectors and find items close in meaning , not just wording. But raw nearest-neighbor retrieval has a blind spot. The vector-closest result might be a tangential paper that happens to share vocabulary, while the genuinely useful one sits slightly further out. Distance in embedding space is a proxy for relevance — a good one, but not the whole story. If you stop at "closest vector," your search is clever and still frustrating. Ranking on top of retrieval The Atlas runs ChromaDB vector search with Sentence-Transformer embeddings across sources like OpenAlex and GitHub — that's the retrieval layer, the "what's semantically near this query." On top of it sits a custom relevance score that decides what actually surfaces first. That two-stage shape is the pattern behind every search system worth using: Retrieve broadly by meaning. Vectors pull in the semantically-relevant candidate set, fast, across a large and varied corpus. Rank deliberately. A custom scoring layer reorders those candidates by what's actually useful — because the job isn't to return related results, it's to return the right one first. Unify the sources. Papers, code, and governance material ranked into a single relevance-ordered experience, so discovery crosses formats instead of siloing them. Why this is the interesting part Retrieval gets the attention; ranking gets the results. Anyone can wire up a vector database and get "se