Cloud & data
EmbeddingGemma 2: making business documents easier to search
Semantic search can help teams find scattered information, but deployment starts with document quality and access rules.
Google introduced EmbeddingGemma 2, an open multimodal embedding model that represents several content types in a shared space.
The KIMY perspective
Internal search is useful only when results are authorized, current and traceable. Before selecting a model, identify authoritative documents and their access rules. An employee should not discover a confidential file through a generated summary. We recommend collecting real questions and comparing results with the existing search experience. Include outdated documents, duplicates and terminology specific to your business. A convincing demonstration is not a substitute for this validation or for deciding who maintains the document collection.
What to check
- Start with a limited corpus and understood access permissions.
- Require a document reference for useful results.
- Evaluate French, English and Arabic retrieval as needed.