Two-Step Contextual Enrichment

Two-Step Contextual Enrichment

TSCE is model-agnostic and increases LLM accuracy +20-30pp

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This repo is for the demonstration of TSCE principles. - AutomationOptimization/tsce_demo TSCE is an open source framework that increases the accuracy and reproducibility of LLM's and AI agents. Run more than 4000 test prompts, noted an uplift of +10 - +30pp
Two-Step Contextual Enrichment gallery image
Two-Step Contextual Enrichment gallery image
Two-Step Contextual Enrichment gallery image
Two-Step Contextual Enrichment gallery image
Two-Step Contextual Enrichment gallery image
Two-Step Contextual Enrichment gallery image
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Anima - Vibe Coding for Product Teams
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What do you think? …

kaleb cadenhead

Been building AI agents and agentic workflows since early 2023. Had a repeat issue where I'd find I could incorporate AI into a workflow in novel ways, but the output was too unreliable to use it at scale. Went back to the drawing board, read up on some other methods similar to this, and thus TSCE was born!