That is a very high volume, especially for being in development. Here are a few things we have done... * Use local machine learning models wherever possible.

That is a very high volume, especially for being in development. Here are a few things we have done... * Use local machine learning models wherever possible. * Summarize and consolidate calls whenever possible (i.e. reduce token sizes using language analytics). * Log all calls/responses so it is possible to reuse them and/or to train your ML models. This can cut down on duplicate calls. * Monitor your API call logs to make sure the system isn't making calls it shouldn't. * Throttle your calls by introducing delays/bottlenecks in the user interface (by far my least favorite). * Charge more for your services to decrease demand. * Contact your account rep and see what options they have to offer with a higher price tier.