Enterprise LLM Costs Out of Control? The Real Culprit Isn't Your Model

Most teams blame expensive models for soaring LLM costs, but this case study reveals the true cause: context inflation from duplicated data, overlapping retrieval results, and unnecessary metadata flooding production systems. The critical finding is that response quality remained virtually unchanged while costs plummeted—proving the problem lies in system architecture, not model selection. This insight reshapes how enterprises should approach AI system design and memory management.