Optimizing LLM Context Windows for Large Enterprise Codebases

We are scaling out our indexing framework across an internal library of approximately 4 million lines of code. The latency overhead during full-context lookups is reaching bottleneck parameters. Are teams finding higher efficiency metrics running tiered semantic chunk sub-clusters, or pushing directly into ultra-large raw context allocation targets?