Hybrid Search Scoring: Balancing Sparse, Dense, and Metadata Signals Hybrid search is where retrieval stops being a single technique and becomes a system decision. A modern stack often has at least three signal families available at query time: **Sparse lexical signals** that reward exact terms and term statistics. **Dense semantic signals** that reward meaning similarity […]

Retrieval Evaluation: Recall, Precision, Faithfulness Retrieval is the part of an AI system that decides what the model is allowed to know in the moment. If retrieval fails, a grounded system becomes an ungrounded system, even if the language model is strong. That is why retrieval evaluation is not a side task. It is a […]

Semantic Caching for Retrieval: Reuse, Invalidation, and Cost Control Retrieval systems tend to become expensive for the same reason they become useful: they get called everywhere. Once retrieval is the default way to ground answers, power assistants, and surface organizational knowledge, the traffic pattern changes. The system starts receiving repeated questions, near-duplicates, and variations that […]