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A DuckDB extension where you can use Jev to do quick classification of rows

Hamilton Ulmer built a DuckDB extension that uses TypeSafeAI's Jev to classify rows in any CSV, Parquet file, or DuckDB table, processing roughly 1,000 rows in about 10 seconds. Ulmer said the approach is faster than using an LLM and more ergonomic than a classifier, while a commenter noted that treating classification as a retrieval problem with embeddings can reach about 20,000 rows per second on CPU without performance optimization.

read1 min views2 publishedSep 17, 2026
A DuckDB extension where you can use Jev to do quick classification of rows
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Hamilton Ulmer on X: "I made a DuckDB extension where you can use @typesafeai 's Jev to do quick classification of rows in any csv/parquet file or duckdb table about 10sec for 1k rows ~ better than using an LLM, way more ergonomic than a classifier game-changing for data analysis!"

I made a DuckDB extension where you can use @typesafeai 's Jev to do quick classification of rows in any csv/parquet file or duckdb table about 10sec for 1k rows ~ better than using an LLM, way more ergonomic than a classifier game-changing for data analysis!

I made a DuckDB extension where you can use @typesafeai 's Jev to do quick classification of rows in any csv/parquet file or duckdb table about 10sec for 1k rows ~ better than using an LLM, way more ergonomic than a classifier game-changing for data analysis!

For just classification, you can go much faster still by treating classification as a retrieval problem and just using embeddings. We easily hit about 20k rows/sec on CPU without doing any performance optimizations.

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