Companies implement More Like This (MLT) search functionality to find documents similar to a given source document by leveraging semantic embeddings stored as vectors in a search index. This approach improves over classic lexical MLT by enabling retrieval of semantically related documents even when different wording is used. It is applied in scenarios such as related articles, product recommendations, support ticket matching, legal and patent research, and RAG context retrieval. Hybrid search combining lexical and vector methods is common in production to balance exact matches and semantic similarity. Implementations like Manticore Search perform vector lookup directly in the search engine, reducing architectural complexity and improving maintainability.
Use Case
Opening the operator briefing
Pulling the full operator breakdown, tooling context, and verification notes.