The decision
Start with a usage model before looking for a monthly price. Active users, sessions, messages, input length and output length each change the workload. Include retrieved passages and conversation history in the input; the visible question is rarely the whole request.
A worked example
Illustrative assumptions: 200 active users, 3 sessions each month and 4 model requests per session produce 2,400 requests. At 1,500 input tokens and 300 output tokens per request, the totals are 3.6 million input and 720,000 output tokens. These are hypothetical quantities, not measured traffic or a supplier quote. Apply separately verified provider rates to each category.
Alternatives worth weighing
A smaller context, shorter answer or simpler model may reduce spend, but evaluate the effect on the actual task. Caching only helps requests suitable for reuse under the relevant privacy and freshness rules. A normal search interface may avoid generation cost where users only need a document.
Where the plan breaks
Do not ignore retries, document indexing, tool calls, storage, monitoring and support. A per-user allowance needs an enforcement point, not just a pricing-page sentence. Track unusually long requests separately because averages can hide the cases that dominate spend.
Build a workload envelope, not just an average
Extend the illustrative calculation with ordinary, heavy and exceptional sessions. A short policy question may need one retrieval and one answer, while a document comparison may require several model requests and much longer context. Count those requests explicitly. For example, if one quarter of the original 2,400 requests uses twice the assumed input, the input total becomes 4.5 million tokens before retries. The output total stays at 720,000 only if output length and request count are unchanged. These remain planning assumptions.
Keep model usage separate from indexing, storage, extraction, integration and human support. Document whether processing a replacement file reuses existing work or rebuilds the collection. Compare provider quotations using the same workload and currency, with a recorded date for the rates. Avoid placing a current price in a long-lived estimate without stating how it will be refreshed. A clear workbook of quantities can remain useful even when provider pricing changes.
Decide what happens at the spending boundary
A warning threshold and a hard limit have different purposes. A warning gives an owner time to investigate unusual usage. A hard limit prevents additional work, so the product must explain the interruption and provide a useful route such as document search or a later retry. Decide whether the limit belongs to an individual, a customer account or the whole service. Concurrent requests need a shared enforcement point; separate checks can each approve work against the same remaining allowance.
Before launch, test a burst of requests, repeated failures and an unusually long document using fictional input. Check that the limit stops new expensive work while preserving already accepted business records. Record quantities, latency and safe error categories rather than unnecessary conversation content. Assign an owner who can investigate spikes and approve a revised allowance. Review both task quality and usage after a change; a lower bill is not a success if users must repeat every question.
Before you commission the work
What is the worst credible usage pattern? Where is the spending limit enforced? Which quality test protects against a cheap but unhelpful response? Take those assumptions into the AI integration estimate and revise them with real usage.