AI teams hemorrhaging money on expensive frontier models when cheaper alternatives would work just as well

Companies building AI agents and applications are forced to route all queries through expensive frontier models like Claude Fable or GPT-4, even when cheaper models could handle 80%+ of requests with identical or better results. Teams lack visibility into which model is actually needed for each task, wasting thousands monthly on overkill compute. Current solutions either require manual model selection or expensive A/B testing in production.