Text embeddings convert text into numerical arrays called vectors. These are designed to represent meaning and relationships, allowing an application to compare pieces of information. Google notes that the content supplied affects those relationships, so an embedding reflects the representation created from that input. Source: Google Cloud: Text embeddings

Test with real search needs

Use approved sample questions and the documents they should retrieve. Include similar hotel names and differently worded descriptions of the same requirement. This checks whether the representation supports the intended search task rather than merely producing plausible-looking results.

Keep the original source available

Retain a link from each result to the underlying document and its date. Review the original wording before using a retrieved condition in an answer. This gives an adviser something concrete to verify when a search suggests a relevant passage.

Written and updated by Travelgenix. Sources checked on 19 October 2026. Practical advice and examples are Travelgenix editorial guidance.