enterprise-search

Tune BM25 relevance and search ranking by capturing baseline metrics like nDCG@10 or MRR, then applying isolated, one-change-at-a-time adjustments to analyzers and boosts with measured before/after evidence.

Measure search quality and relevance regressions by establishing metric baselines using evaluation pipelines, then enforcing evidence-based gates that validate isolated changes against those captured baselines.

Fix latency bottlenecks across query types through performance optimization workflows that require platform specificity and structured analysis to isolate and resolve slow query execution paths.

Yes, you can configure hybrid vector search and analyzer chains by guiding query understanding and schema mappings with concrete configuration outputs tailored to your specific platform version.

Search ranking tweaks fail in production when changes lack metric-first evaluation, causing weak query understanding and unmanaged index changes that bypass evidence-based regression checks.

Yes, baseline metrics are required before adjusting index management and query DSL to prevent hallucinated configurations, enforce specificity, and ensure measured before/after improvements.