Fenic
fenic.ai
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Overview
Fenic is a semantic DataFrame engine: PySpark/SQL plus AI operators that turn structured and unstructured data into typed, reusable, inspectable pipelines.
News
Why and how we extended Polars with Rust expression plugins for fenic
The text operations an AI pipeline needs - chunking, prompt templating, jq, fuzzy matching, markdown and transcript parsing - aren't in Polars, and Python UDFs are slow and break composition. Here's why we wrote nine Rust expression plugins to extend Pola
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Northwestern grad Steve Fenic has professional affinity for numbers that has made him a big winner
Fezzik, of course, is best known as Fez in the sports-betting business. In reality, his name is Steve Fenic, a 62-year-old native of Dayton, Ohio, who is widely known in this zany industry.
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fenic 0.7.0: Gemini 3 Flash, Granular Thinking Levels - plus session and docs improvements
fenic 0.7.0 adds Gemini 3 Flash Preview with four thinking levels, optional usage summary suppression, and a use-case-first README overhaul.
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fenic 0.6.0: LLM Caching, New Models, DataFrame Ops - plus PDF and Agent upgrades
fenic 0.6.0 adds persistent LLM response caching, Claude 4.5 / GPT-5.1 / Gemini 3 Pro support, 20+ new DataFrame operations, and expands PDF parsing to OpenAI and OpenRouter.
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Why we built fenic
What would a data processing framework look like if we built it today? With modern workloads, unstructured data, and LLM inference as first-class compute.
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