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Case Studies
EyesInAI started as a way to see which AI model is best for which job. The natural next step: use that same benchmarking on a real product. We take a client’s actual tasks, test every candidate model against the real data, and find the cheapest model that still answers correctly— task by task. Here’s the first one.
For an equipment-rental company’s field-service support chatbot, we benchmarked 5 models across 11 chatbot actions and built a routing table: the cheapest model that still gets each task right.
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