As AI providers rapidly iterate, developers struggle to assess new models' performance on their specific use cases.
Build a testing framework that runs standardized prompts across multiple providers and compares outputs on accuracy, cost, and performance.
Paid by engineering teams needing to optimize their AI stack.
MVP could compare just two providers on basic metrics.
Risk is rapid API changes requiring constant maintenance.