Find which features and prompts drive your AI bill, then cut costs with smaller models, shorter prompts, caching and output limits.
My OpenAI bill is way too high. Find where the money goes and cut it
How it works
- Break down spend by model: Vovy opens your usage dashboards and shows a chart of cost by model and day, so you see if one feature or a spike is the culprit.
- Find the expensive calls: Vovy asks Claude Code to find every AI call in your code and estimate tokens in and out for each. Long system prompts and chat history usually dominate.
- Rank savings ideas: A table lists each fix with estimated savings: a cheaper model for simple tasks, trimming history, capping max output tokens, or caching repeat prompts.
- Apply the top fixes: Claude Code makes the changes you approve and Vovy shows the diff. Nothing ships until you say so.
- Compare before and after: Vovy runs the same test inputs through old and new code and shows cost and quality side by side on a card.
What you provide
- Access to your AI provider dashboards
- Your app's code
What you get
- A cost breakdown chart
- A ranked savings plan
- Code changes with measured savings
FAQ
Will a cheaper model make my app dumber?
Only where it matters. Vovy tests on your real inputs, so you only switch tasks where quality holds.
What saves the most, usually?
Routing simple tasks to a small model, and not resending long chat history or giant system prompts on every call.
Could a bug be the real cause?
Often. Retry loops or requests fired on every keystroke can multiply the bill. Vovy looks for those first.
Related tasks
All tasks