Search Relevance Tuning Lab

 Create an interactive Search Relevance Tuning Lab for teams building search across websites, product catalogs, and knowledge bases. Let users import search queries, documents, current results, and human relevance judgments. Compare ranking strategies involving exact matches, synonyms, typo tolerance, recency, popularity, and semantic similarity. Display metrics such as precision at K, recall at K, mean reciprocal rank, and normalized discounted cumulative gain where the necessary judgments exist. Highlight queries with poor results, support side-by-side ranking experiments, and suggest targeted improvements. Include a reproducible evaluation dataset and clear explanations of every metric. Never present untested ranking changes as proven improvements.