SOURCE-LINKED INTELLIGENCE
SAGE: Governed Artifact Generation from Enterprise Guidelines
Enterprise guideline documents mix narrative text, complex tables, and embedded images, and converting them into structured work artifacts still takes two to three days of manual effort each. Current language and vision-language models extract from such documents but offer no governed workflow beyond extraction: no validation, no consistency checking, no traceable artifact generation. We introduce SAGE, a governed multi-stage LLM pipeline organized around a shared versioned rule store with stable identifiers, schema-validated inter-stage contracts, and end-to-end provenance tracking. Extracted
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-15T19:37:46.000Z
First collected: 2026-09-20T08:20:57.646Z. This is not the publication date.