Production AI cost audits that reduce inference spend 8–20×. Claude / Anthropic, OpenAI / GPT, and self-hosted LLM optimisation across orchestration, prompting, caching, and governance.
Per-call observability, tiered model routing, prompt and context discipline, orchestration cleanup, caching strategy, and cost governance. Benchmarked against seven cost layers.
8× to 20× across 20+ Skopa engagements. Median ~12×. Roughly 30% of savings come from orchestration, 25% from prompt and context, 20% from model selection and routing.
CTOs, VPs of Engineering, AI platform leads, and FinOps teams whose monthly inference spend has crossed a five-figure threshold and is still trending up.