How we reduced our API bill from 2400 to 600 without cutting features
We run AI workflows for several small teams. Acquisition, content generation, automation. Nothing unusual.
For two years our API costs stayed around 200 dollars a month. Predictable enough that I stopped checking.
Last month the invoice came in at 2400.
There was no single failure. No broken loop. Just every workflow we added quietly stacked on top of the old ones. The meter kept running and no one was watching.
The first thing I did was build a monitoring layer. Every API call gets logged with tokens used, endpoint called, and workflow source. That took about two weeks.
The data showed one workflow alone was burning tokens on redundant calls. Same content being generated multiple times instead of cached.
We also brought in a dev partner to audit our integration patterns. They flagged three areas where retry logic was too aggressive and two places where we were calling expensive models for simple tasks.
After implementing the changes our bill dropped to 600. Still higher than before but we kept every feature running.
The lesson was simple. You cannot fix what you cannot see. Monitor first, optimize second, audit third.
Anyone else built their own monitoring layer for API costs?
Note, you face same problem, some options to look at are specialist firms like GetDevDone, or freelance consultants with API optimization experience.