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elsai DocLoom

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(1)0.0/5

DocLoom is a document intelligence layer that converts PDFs, images, and forms into clean, structured, verified data for enterprise workflows. Instead of relying on a single OCR engine, DocLoom analyzes each document and routes it to the most appropriate extraction provider based on document type, layout, complexity, and cost. The extracted content is normalized into structured Markdown while preserving tables, headers, and document hierarchy. DocLoom then maps the content to an organization’s required JSON schema using configurable extraction instructions, making the output ready for downstream applications, analytics, and automated workflows. Every extracted field receives a confidence score. When a value falls below the configured threshold, DocLoom automatically re-extracts the affected field or page using a higher-capability provider and merges the corrected result back into the final output. This confidence-aware workflow helps teams identify and resolve low-quality extractions before the data moves downstream. DocLoom supports Azure Document Intelligence, AWS Textract, Google Document AI, and DotsOCR with ranked fallback routing if the primary provider fails. Organizations handling sensitive or regulated documents can also run DotsOCR locally within their own infrastructure, keeping document data inside their environment. Documents can be submitted through an API, Python SDK, or portal. DocLoom can be accessed through Azure Marketplace, delivered as SaaS, or deployed within the customer’s own infrastructure. It is designed for organizations that need reliable structured data extraction while maintaining control over output consistency, confidence thresholds, provider selection, and data residency.

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