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PULSAR system enhances enterprise visual document search with pooled indexing

By PulseAugur Editorial · [1 sources] ·

A new research paper introduces PULSAR, a vision-first retrieval system designed for enterprise visual document RAG. Deployed at Mubadala Investment Company, PULSAR uses a pooled, late-interaction index to efficiently search dense documents like pitch decks and board packs. This approach significantly reduces latency and cost compared to traditional OCR and verbalization methods, while maintaining high retrieval accuracy. Since its deployment in March 2026, PULSAR has processed a substantial volume of documents and pages across numerous deals, improving answer-fact recall. AI

IMPACT This system could significantly improve how financial institutions and other enterprises search and extract information from complex visual documents.

RANK_REASON The cluster describes a research paper detailing a new system for information retrieval. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.IR (Information Retrieval) →

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

PULSAR system enhances enterprise visual document search with pooled indexing

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The cluster describes a research paper detailing a new system for information retrieval. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Aidan Millar ·

    PULSAR: Pooled Unified Late-Interaction Search and Retrieval for Enterprise Visual Document RAG

    Institutional investors search visually dense pitch decks, board packs, and diligence materials that change hourly near deal closing. OCR followed by figure verbalisation is costly to refresh at this scale and can lose chart detail. We present PULSAR, a production vision-first re…

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