EDUCATION & TRAINING
How We Blew Up the Docs and Built a System That Actually Works
Dev.to Machine Learning
About This Tutorial
The Problem We Were Actually Solving Our users werent doing semantic search. They were executing treasure hunts: complex, multi-stage queries where the first phase returned 200,000 candidate docs for phrase matching, and the second phase had to rank them by exact term proximity, metadata filters, and user-defined boosts. The Veltrix docs treated this as an afterthought. Their example pipeline assumed a single-stage recall-then-rank flow with no custom scoring hooks.