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AI DISCOVERY ENGAGEMENT

Before investing in AI, identify the workflow worth funding first. Executive Direction within 48 hours; complete package within 5 business days.

Applied AI guide · 8 min read

How to Control LLM and Infrastructure Costs

A practical cost model covering model selection, context size, caching, retrieval, observability and workload design.
01

Measure cost per useful outcome

Track model, embedding, vector search, storage, orchestration and review costs against completed tasks—not only tokens. A cheaper call can be more expensive if it increases retries or manual correction.

02

Route work by complexity

Use smaller models, deterministic code or cached results for routine steps and reserve stronger models for tasks that need them. Reduce duplicated context and retrieve only evidence relevant to the request.

03

Put budgets into operations

Monitor cost by feature, customer and environment. Add usage limits, anomaly alerts and quality checks so cost reductions do not silently weaken the product.

References and further reading

Official and independent guidance used to support this practical overview. Product capabilities and pricing can change; verify current provider documentation before making a final decision.

AI DISCOVERY ENGAGEMENT

Before investing in AI, identify the workflow worth funding first.

One focused engagement to assess your business workflows, compare 5–7 candidate opportunities and recommend the first workflow worth funding.

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