# How do you plan API token usage forecasts and spending alerts during fine-tuning?

I liked that AddWeb Solution Private Limited integrated production-grade MLOps early, including hallucination and data-drift monitoring, which reduced risk during a global rollout. I struggled with limited budget visibility during fine-tuning and would have wanted a more detailed API token usage forecast plus earlier spending alerts. The AI agents also helped reduce manual work in customer support, inventory management, and code quality, improving efficiency and delivery speed. How are others handling token forecasting and cost alerts while scaling AI agents?

##### Post Metadata
- Posted at: 28 days ago
- Author title: Co-founder &amp;amp; MD at SPREAD AI
- Net upvotes: 1


## Comments
### Comment 1

To give a bit more context: during the fine-tuning phase we saw API token costs fluctuate more than expected, even though the overall project stayed within budget. A clearer forecast model and automated spending alerts from the start of that phase would have made internal tracking much smoother.
Curious to hear how other teams are handling token cost visibility when scaling AI agents in production.
Any practical setups or tools that worked well for you?

##### Comment Metadata
- Posted at: 28 days ago
- Author title: Co-founder &amp;amp; MD at SPREAD AI




## Related Product
[AddWeb Solution Private Limited](https://www.g2.com/products/addweb-solution-private-limited/reviews)

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