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I'm as LLM reliant as the next person.. But we forget there are other models too, specialized models that are cheaper and more effective to use depending on the task.. E.g.: Agents need tools for structured data predictions.

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LLMs handle reasoning and orchestration. But when it reasons that it needs to predict an outcome based on structured data, it should also reason about routing to an appropriate tool: a tabular foundation model.

Tabular foundation models work as a prediction tool in agent workflows. The agent passes it structured data and a prediction task. Our TFM at @prior_labs - TabPFN uses historical structured data as context and returns results, in a single forward-pass.