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Introducing prompt_jev(): bringing Jev to MotherDuck SQL
MotherDuck adds a native SQL function for Jev to perform high-scale text classification without external model parsing.
What: The new `prompt_jev()` function in MotherDuck enables text scoring and classification directly within SQL queries. In a 100,000-row benchmark, the function achieved 89% accuracy at a cost of $0.50.
Why it matters: Integrating decision models directly into SQL at the engine level removes the latency and cost overhead of sending large datasets to an external LLM via API.
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