Rivac LabsLLM Cost Optimization, Routing & Caching
LLM bills tend to climb faster than usage would explain, usually because every request — simple or complex — is going to the same expensive frontier model by default. This service engineers that spend down: intelligent routing that sends each request to the cheapest model capable of handling it, response caching for repeated or near-duplicate queries, and request batching where latency allows, all validated against your actual quality bar so cost drops without anyone noticing a difference in output. It's for teams whose inference spend is growing faster than their traffic, or who've never questioned whether every request needs the biggest model available. The deliverable is a routing and caching layer with measured savings attached to it, not a suggestion to try a smaller model.
How We’d Approach This
A clear, staged plan — not a black box
- 1
Diagnose current token spend by request type, model, and endpoint to find where cost is concentrated and misallocated.
- 2
Pilot model routing and caching on the highest-volume request type, measuring quality against the existing baseline.
- 3
Review cost savings and quality metrics with stakeholders to confirm the quality bar holds before routing more traffic.
- 4
Roll out routing, caching, and batching across remaining request types, with a dashboard tracking savings over time.
What You Get
Deliverables from this engagement
- Token-cost audit broken down by request type and model
- Intelligent routing layer sending requests to the cheapest capable model
- Response caching and request-batching implementation
- Cost-savings dashboard with before/after spend comparison
Six Ways We Could Architect This
Different engagement, different build — pick the shape that fits
There’s more than one way to deliver on this service. Browse a few of the ways we’d structure the work, depending on your speed, budget, and integration needs.
Ready to get started?
Tell us what you’re trying to get done and we’ll help you find the highest-leverage place to start — scoped small enough to prove itself before you commit to anything bigger.
Talk to us about LLM Cost Optimization, Routing & Caching