Deploying LLM Pipelines Without Breaking the Bank

The Cost Problem in Production AI

Production inference cost depends on traffic, prompt and response size, model mix, retries, evaluation, and supporting infrastructure. Build a workload-specific cost model and measure it under representative load before setting a budget.

Semantic Caching

Semantic caching can reduce repeated inference for suitable workloads, but savings and quality effects vary. Evaluate hit rate, freshness, authorization boundaries, invalidation, privacy, and answer quality before enabling it.

Model Routing

Not every request requires the same model. Routing may reduce cost, but each route needs quality, safety, latency, and fallback evaluations on representative tasks. Report measured savings for the selected workload rather than a generic percentage.