Since generative AI exploded, it's all anyone talks about. But traditional ML still covers a vast space in real-world production systems. I don't need this tool right now, but glad to see work in this area.
For example CV triage, you use a LLM with a rubric to extract features, choosing the features you are going to rely on does a lot of work here. Then collect a few hundred examples, label them (accept/reject) and train your trad ML model on top, it will not have the LLM biases.
You can probably use any LLM for feature preparation, and retrain the small model in seconds as new data is added. A coding agent can write its own small-model-as-a-tool on the fly and use it in the same session.
Unless by LLM feature extraction you mean something like "have claude code write some preprocessing pipeline"?