Authority guide

How to Run a 14-Day LLM Cost Control Pilot

A step-by-step pilot plan for validating LLM cost savings without weakening answer quality.

The problem

AI spend often grows faster than governance because teams ship prompts, RAG workflows, agents, model routing and GPU serving before finance has a practical control model.

The ML Mind approach

ML Mind separates visibility from control. It starts by identifying where spend leaks, then recommends the least invasive control that can reduce cost while protecting answer integrity.

Safe savings are not blind reductions. They are savings that survive quality, trust and operational checks.

Practical next step

Run the readiness checklist, generate a savings estimate, then request a free audit to validate the largest opportunity against real usage data.