As European search applications scale, they face a unique challenge: maintaining high-concurrency relevance across multi-lingual datasets. When an index grows to 25GB+, standard Lucene merge policies often lead to "Segment Fragmentation," causing significant latency spikes in k-NN search. This session moves beyond basic vector implementation to perform "surgery" on the underlying Lucene engine. We explore how to tune index merge policies and custom analyzers specifically for multi-lingual shards, ensuring that 60+ concurrent streams remain performant. Attendees will learn how to optimize the physical storage of vector data to reduce I/O overhead and maintain sub-second relevance without bloating hardware costs.