Where LLM costs actually come from
Almost every hosted LLM bills by tokens — the text going in and coming out. So your bill is driven by how many requests you make, how long your prompts are, how much context you stuff in, and which model tier you call. The biggest waste is usually paying premium-model prices for requests a smaller model could handle.
Before changing anything, we measure where your spend goes by request type. You can't optimize a bill you haven't broken down.
- Costs scale with input + output tokens, model tier, and request volume
- Long system prompts and large retrieved context are silent budget drains
- Retries, looping agents, and verbose outputs multiply spend
- The first step is a per-endpoint breakdown of tokens and dollars
The levers we pull
Most savings come from a handful of well-known techniques applied carefully. The art is doing it without degrading answers — we test the changes against your real traffic so quality holds.
- Caching: exact-match and semantic caching so repeated questions don't re-hit the model
- Prompt caching: reuse a fixed system prompt or context at a discount where the provider supports it
- Model routing: cheap/small model for easy requests, premium tier for the hard ones
- Prompt trimming: shorter instructions and tighter retrieved context
- Output limits: cap response length and use structured outputs to avoid rambling
- Batching and streaming where they cut cost or improve perceived speed
Cutting spend without breaking quality
Cost cuts are only real if answers stay good. We treat every change as an experiment: define what a correct answer looks like, measure before and after, and roll back anything that hurts accuracy.
We also set budgets and alerts so you see spend in real time instead of discovering it on the invoice.
- An evaluation set so 'cheaper' never quietly becomes 'wrong'
- Spend dashboards and alerts by feature and by customer
- Fallback logic when a cheaper model isn't confident
- Right-sizing self-hosting only when volume genuinely justifies it
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Frequently asked questions
How much can you actually save us?
It depends entirely on how your current system is built — we won't quote a percentage we can't back up. Systems that route everything to a top-tier model with long prompts usually have the most room; a lean system may already be near optimal. The consultation includes a look at where your spend is going.
Will a cheaper model make the answers worse?
Only if we let it. We route to smaller models only for requests they handle just as well, and we verify that with an evaluation set against your real traffic. Anything that measurably hurts quality gets reverted.
Do we need to switch providers?
Usually not. Most savings come from how you use your current provider — caching, routing, and prompt design. If a switch would genuinely help we'll say so, but it's rarely the first move.