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IJONIS
Data & Infrastructure

Semantic Search

Semantic search is a search technology that looks for the meaning of queries rather than exact keywords. It uses embeddings and vector databases to find contextually relevant results — even when terminology differs from the search query. For enterprises, it replaces rigid keyword searches with intelligent understanding.

Why does this matter?

Employees spend an average of 20% of their working time searching for information. Semantic search drastically reduces this: "What warranty cases occurred in Project Mustermann?" finds results even when documents refer to "claims" or "guarantee" instead of "warranty." This measurably boosts productivity.

How IJONIS uses this

We implement hybrid search architectures combining semantic vector search with classic full-text search — for optimal results with technical terms and natural language alike. Reranking models prioritize the most relevant hits, and facet filters enable additional narrowing by date, type, or department.

Frequently Asked Questions

Does semantic search work reliably in German?
Yes, with the right embedding models. We test multiple models specifically for German-language texts and select the one with the best recognition rate for your technical vocabulary. Multilingual models like E5 or BGE-M3 achieve excellent results in German as well.
How does semantic search differ from a classic Elasticsearch search?
Elasticsearch finds documents through word matching and TF-IDF scoring. Semantic search understands query meaning and finds results with different phrasing. In practice, we combine both: Elasticsearch for exact matches, vector search for semantic understanding.
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