{"article":{"annotation":{"article_id":"agentcore-self-improving-document-processing-idp-2026","available_at":"2026-10-15T20:48:42.871893Z","geography_revision":"ef6ee0010dda5fe7b240fd514749b43e214c57da73222d2e40ec83b276dd0977","id":"17263f0087bd19743775533627a6a5535e0d7724a53e998548fdb538450039e2","input_sha256":"cff0991739eb7835a2694e1f0448f95740b09ea8ed24cedd299a06827160aca4","limitations":["Rule-derived subjects are candidates, not verified editorial labels or calibrated model probabilities.","Coverage is distinct from event location. 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Oktober beschreibt einen Multi-Agenten-Ablauf für Dokumente wie Lieferantenrechnungen mit wechselnden Layouts. Ein Analyse-Agent extrahiert Text und erkennt den Dokumenttyp, ein Abgleich-Agent findet ähnliche Datensätze; Extraktions- und Prüf-Agenten vergleichen die Angaben mit Geschäftsregeln.","Die Architektur nutzt Textract, S3 Vectors, Aurora DSQL und AgentCore. Anweisungen für neue Formate können bei ähnlichen Dokumenten erneut verwendet werden. AWS beschreibt einen Implementierungsleitfaden und veröffentlicht keine unabhängigen Genauigkeitswerte für jeden Dokumenttyp."],"sections":[]},"corrections":[],"country":null,"data":{"blocks":[{"description":{"ar":"نشرت AWS في 14 أكتوبر دليلاً تقنياً لمعالجة الوثائق المتعلمة باستخدام AgentCore.","de":"AWS veröffentlichte am 14. 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