Semantic Search and Vectors support on Dynamics 365 Business Central: this is the right moment.

Dynamics 365 Business Central

The article discusses the implementation of a semantic search feature for Dynamics 365 Business Central during the AI Hackathon.
Semantic search interprets the meaning of words and phrases to provide more relevant search results compared to traditional full-text search.
Vector representations and embeddings are used to enable semantic search by converting discrete entities into numerical vectors.
Cosine similarity is utilized to measure the degree of similarity between vectors in a multidimensional space.
Azure SQL now natively supports vectors, allowing for efficient storage and retrieval of vector data.
New SQL functions introduced in the platform enable operations on vectors stored in binary format, enhancing data analysis capabilities.
The implementation of cosine similarity between vectors at the SQL level significantly improves search performance in Business Central.
The author suggests that it is the right time to consider implementing semantic search capabilities natively in Dynamics 365 Business Central to leverage Azure SQL's vector support.

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