Original canonical engineering research published at Botmartz Insights: Why Vector Similarity Is Not Semantic Search .

Why Vector Similarity Search Is Not Semantic Search: The Mathematical and Architectural Foundations of Production Retrieval

Executive Summary

The default architecture promoted across contemporary machine learning tutorials and developer documentation asserts a straightforward premise: convert unstructured text into dense floating-point vector embeddings, index them within an Approximate Nearest Neighbor (ANN) vector database, and retrieve top-$k$ candidates via cosine similarity.

In enterprise software engineering, this naive bi-encoder retrieval model regularly degrades in production.…