Razuna is equipped with an advanced semantic search engine that significantly enhances users' discovery of relevant files within your dataset. Unlike traditional keyword-based searches, which require users to know the exact terms or phrases associated with the files they seek, semantic search operates on a deeper understanding of the concepts and relationships behind the words.
Here is a short introduction video to how the semantic search works.
This innovative search capability allows users to retrieve results based not only on exact matches but also on the contextual significance and conceptual relevance of their queries. For instance, if a user enters the term "ocean" and your dataset only includes the keyword "sea," a semantic search engine will recognize the inherent relationship between the two concepts and still return results related to "sea." This means users can find what they need even if they are unaware of the specific terminology in your files.
By leveraging semantic associations, Razuna makes information retrieval more intuitive and efficient. It enables users to fully explore the content of your datasets without being limited by language or phrasing barriers. This ensures that they uncover relevant files that might otherwise be overlooked in a traditional search scenario, ultimately leading to a more streamlined and effective search experience.
There's no need to configure or adjust any settings for the semantic search, as it operates automatically in the background. To achieve the best results, please provide a meaningful file name and description, as the semantic search builds its index based on these two fields.
The semantic search is driven by an AI model hosted on our network. We do not share your data with any third parties.