Why AI bills surprise people
Most AI APIs charge by tokens — roughly, the amount of text in and out. Costs creep up because prompts get bloated, the biggest model gets used for every task, the same questions get re-answered from scratch, and nobody's watching per-request cost.
Each of those is fixable once you can see it.
- You pay per token, in and out — length is money
- Oversized prompts and stuffed context inflate every call
- Using a top-tier model for trivial tasks wastes money
- Re-answering identical questions instead of caching
- No visibility into which feature costs what
The levers that actually cut cost
A few techniques do most of the work. Cache repeated or similar requests. Route each request to the cheapest model that can handle it, reserving the expensive one for hard cases.
Trim prompts and use retrieval to send only relevant context, and lean on provider features like prompt caching where they exist.
- Caching identical and semantically similar requests
- Model routing: cheap model first, escalate only when needed
- Prompt trimming and retrieval so you send only what's relevant
- Provider prompt-caching for repeated context
- Batching where latency allows
- Max-output limits to stop runaway responses
Measure, then optimize
You can't control what you don't measure. We instrument usage per feature and per request, set budgets and alerts, and optimize the expensive paths rather than guessing.
Often a large share of cost comes from a small number of call patterns — fix those and the bill drops.
- Per-feature and per-request cost tracking
- Budgets and alerts before a surprise invoice
- Identify the few patterns driving most of the spend
- Rate limiting and abuse protection
- Ongoing re-evaluation as model prices change
More on ai integrations
Frequently asked questions
What's the single biggest way to cut AI costs?
Usually model routing plus caching. Sending easy requests to a cheaper model and not re-answering repeat questions often cuts a bill substantially, without hurting quality on the hard cases.
Will optimizing for cost make the AI worse?
Done well, no. The goal is to spend on the requests that need a strong model and stop overpaying on the ones that don't. We measure quality alongside cost so you're not trading one for the other.
Can you tell me exactly what I'll pay?
Not without knowing your volume, models, and prompt sizes — those are the real drivers. We'll estimate against your expected usage in a free consultation and build in tracking so it stays predictable.