Want to see the practical retrieval examples? Jump to the ten real English retrieval examples. Executive Summary Our earlier German MIRACL benchmark showed that linguistic analysis can substantially improve lexical search in a morphologically complex language. The...
Vector search, also known as semantic search, has transformed enterprise search in the past few years by retrieving information according to meaning rather than relying exclusively on exact words. It is particularly effective when users and documents express the same...
Executive Summary In a search benchmark for German, Bitext Linguistic Analysis SDK returned more relevant results and missed fewer useful passages than every tested Elasticsearch configuration. In short, Bitext Linguistic Analysis improves German search quality by up...
Stemming kills AI Accuracy: Why German Search Needs Lemmatization Search systems have relied on stemming for decades. The reason is simple: stemming is fast, easy to integrate, and widely available in engines such as Elasticsearch, OpenSearch, Solr, and other...
Most teams working with Elasticsearch, OpenSearch or RAG pipelines focus on ranking, embeddings or model quality when trying to improve relevance. But in many cases, the issue starts much earlier: in how text is normalized before indexing. In a previous post, we...
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