LLM cost optimization for existing AI stack
Audit, reroute, and cache your way to 40-60% cost reduction — without changing outputs.
We audit your current AI workload, identify cost hotspots, and implement multi-model routing, semantic caching, prompt compression, and request batching. Zero degradation in output quality — just significantly lower bills.
- Which requests are over-served by premium models?
- Where can caching safely reduce repeat inference?
- How do we A/B test cost optimizations without outage risk?
- How do we monitor cost per feature going forward?
- $10k+/month LLM spend
- Existing production system
- Quality-sensitive workloads
What shipping this looks like.
The typical tools for this use case.
Every engagement picks the right tool for your context — these are defaults, not prescriptions.
Services that deliver this use case.
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Thinking about llm cost optimization for existing ai stack?
Book a 30-minute scoping call. We'll tell you what shipping this looks like for your context.