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New SAGE system automates artifact generation from enterprise guidelines

Researchers have developed SAGE, a new multi-stage LLM pipeline designed to automate the generation of structured work artifacts from complex enterprise guideline documents. This system incorporates a governed workflow that includes validation, consistency checking, and provenance tracking, significantly reducing the manual effort and time required for this process. SAGE aims to improve accuracy and efficiency by identifying and flagging uncertain or contradictory information for human review, while auto-approving high-confidence outputs. AI

IMPACT Automates complex document processing, potentially reducing manual labor and improving compliance in enterprise settings.

RANK_REASON This is a research paper describing a novel system and its evaluation. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New SAGE system automates artifact generation from enterprise guidelines

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This is a research paper describing a novel system and its evaluation. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Mohammadreza Sediqin, Shivali Dalmia, Sumukha Thoppanahalli, Srinivasa Karthikeya Reddy Kovvuri, Abhishek Mukherji ·

    SAGE: Governed Artifact Generation from Enterprise Guidelines

    arXiv:2609.17775v1 Announce Type: new Abstract: 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 mod…