Elasticsearch 7.0 introduces new tools to simplify relevance tuning, a challenging task often hindered by the need for extensive human-annotated training sets. The update includes the addition of the rank_feature and rank_features fields, which improve relevance metrics by facilitating efficient ranking queries based on non-textual signals like popularity or authority. These fields support top-k retrieval optimizations, allowing for quicker retrieval of top matches without sacrificing performance. Additionally, the Script Score Query enhances flexibility by allowing users to define custom scoring formulas through Painless scripting, accommodating various relevance signals such as numeric, geo, or vector fields. These innovations aim to streamline the process of improving search relevance while maintaining query performance, with the promise of future developments for dynamic features like recency or geo-distance.