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Inference
Running a trained model to produce useful output.
companion card
Inference is the act of running a trained model to produce an answer, tool call, embedding, or prediction.
What it means
A request enters the serving stack, the model computes likely outputs, and the product receives generated text, structured data, embeddings, or tool calls.
Why product teams care
The model is only part of inference. Prompt size, retrieval, tools, batching, streaming, and provider health all shape the user experience.
Understudy angle
Understudy focuses on repeated inference workflows: capture them, measure them, optimize cheaper paths, and keep routes observable.
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Inference is where quality, latency, cost, and product experience meet.
Log input tokens, output tokens, latency, cost, and pass/fail for one workflow.