How to think about LLM Gateway and ML Mind
| Question | LLM Gateway | ML Mind |
|---|---|---|
| Primary focus | Visibility, gateway or developer workflow depending on deployment. | Safe savings control across tokens, RAG, retries, cache, routing, GPU and training. |
| Core buyer question | What happened in my LLM app? | Where is AI spend leaking, what can we safely reduce, and what should we control first? |
| Risk handling | Often requires separate evaluation and governance setup. | Uses integrity-adjusted savings: cost reduction counts only when answer integrity is preserved. |
| Best fit | Teams that need observability or gateway capabilities. | Teams that need a measurable AI FinOps and savings program. |
Unsure which category you need?
Run a free audit to identify whether your first step should be visibility, RAG optimization, routing, cache, retry prevention or GPU control.