Start with the cost of a useful outcome
A monthly total tells you what you paid. It doesn't explain which customer action drove it. We map the costly journeys: generated answers, document processing, repeated background work, data transfer and always-on infrastructure.
Where the available usage data permits, we connect activity to cost and look for avoidable repetition. We distinguish an app growing normally from a retry loop, misuse or a configuration that leaves resources running unnecessarily.
Where we look for improvements
Cheaper is not automatically better. We compare any proposed change with the quality and behaviour your users need, then verify it on a representative task before rolling it out broadly.
- Model choice and context size relative to the job being done.
- Duplicate requests, unbounded retries and work triggered more often than intended.
- Caching or reusing results when freshness and privacy allow it.
- User quotas, request limits and bounds on uploads or generated output.
- Infrastructure size, idle services, storage growth and transfer costs.
- Visibility into usage, with alerts someone knows how to act on.
Make the limits do real work
A budget notification may only tell you that spending has passed a threshold. We check which provider controls actually stop work and where the app needs its own limits. Expensive server endpoints should check identity, entitlement and allowed usage before making the paid call.
We also plan the customer experience at a limit: a helpful explanation, a bounded retry or a clear next step. Silently failing after taking someone's input is a poor trade for a smaller bill.
Review first, change with evidence
A Nap can identify the main cost drivers and recommended controls. Power Nap can implement agreed changes and help verify the result. Ongoing reviews fit Deep Sleep when usage patterns and features keep changing.
We don't promise a percentage saving without evidence. What is possible depends on your workload, existing efficiency, quality requirements and provider pricing. The goal is a more understandable cost base and fewer avoidable surprises.
A few fair questions.
Can you help with a sudden AI bill?
Yes. We can review usage and the request paths behind it, then agree investigation and containment work. If spending is actively continuing, use the provider's available controls while arranging help.
Will you just switch to the cheapest model?
No automatic switch. We assess the task and compare quality, latency and cost. Smaller inputs, fewer repeated calls or better limits may be more useful than a model change.
Do rate limits solve the whole problem?
They are one control. Per-user allowances, input and output bounds, retry behaviour and server-side permission checks can all matter. Controls should match how the app incurs cost.