はじめに デジタルトランスフォーメーション（DX）が加速する現代において、ドキュメント処理の自動化は多くの企業にとって重要な課題です。特に、請求書や契約書といった非構造化データからの情報抽出は、生産性向上の鍵を握ります。 この課題に対する有力な解決策の一つとして、Micr...

Unveil the future of document intelligence with ExtractThinker, combining ORMs and LLMs

はじめに デジタルトランスフォーメーション（DX）が加速する現代において、ドキュメント処理の自動化は多くの企業にとって重要な課題です。特に、請求書や契約書といった非構造化データからの情報抽出は、生産性向上の鍵を握ります。 この課題に対する有力な解決策の一つとして、Micr...

In today’s data-driven enterprises, critical business information often arrives in the form of PDFs—bank statements, invoices, policy documents, reports, and contracts. Although these files contain valuable information, turning them into structured, reusable data or finalized business documents often requires significant manual effort and is highly error-prone. By leveraging Azure Document Intelligence (for PDF data extraction),

Mistral's fourth-generation OCR model returns bounding boxes, block classification, and confidence scores as first-class outputs, eliminating a costly integration layer for enterprise document pipelines. At $4 per 1,000 pages with self-hosted deployment, it's a direct challenge to U.S.-jurisdiction

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In effort to streamline and automate processes, and make more informed decisions around claims applications, VGM engaged the team at SPR to create machine learning models that would support them in gaining valuable insights based on historical application and claim data.