Enterprises need to self‑host large language models to meet data‑residency requirements, yet supporting diverse internal applications fragments a limited GPU pool. The authors consolidate traffic from over 200 internal services onto a single model by closing quality gaps identified through production error analysis on instruction following, function‑calling, and internal task distribution. Offline benchmarks stratified across these axes track the resulting quality improvements.