1
Observe
See spend, tokens, providers, latency and retries. Best for teams that want visibility without architecture changes.
2
Optimize
Reduce context and RAG waste before inference while protecting critical facts and citations.
3
Control
Use gateway-level controls for routing, cache, retry prevention, fallback and verification.
4
ModelOps
Reduce GPU serving waste across self-hosted models, batching, replicas, OOM loops and idle capacity.
5
Lifecycle
Govern fine-tuning and training cost with experiment deduplication, early stopping and release gates.
Why maturity matters
ML Mind does not require every customer to start as a full gateway. The right starting point depends on what data is available, how much risk the team can accept, and which waste source is largest.
Lower riskStart with visibility.
Faster proofTarget the largest waste source.
Better trustMeasure savings with integrity.