Semantic search
Search that finds results based on meaning rather than exact keyword matches, usually by comparing embeddings of the query and the content. It can find a relevant passage even when it uses different words from the question.
Why it matters
Staff rarely know the exact terminology used in policies, contracts or technical documents. Semantic search helps them find relevant material and underpins most retrieval-augmented generation systems.
It has weaknesses: it can miss exact identifiers such as product codes or clause numbers, and it may rank plausible but outdated content highly. Combining it with keyword search and metadata filters usually gives better results.
In practice
For example, an engineering firm’s technical library might let an engineer search ‘corrosion limits for coastal steelwork’ and find a standard that uses the phrase ‘marine exposure class’, with results filtered to the current revision.
Where Rodan fits
Rodan builds search and retrieval over organisational knowledge as part of AI and Decision Systems delivery.