PDocs AI

Architecture

Enterprise document workflow architecture.

PDocs AI transforms incoming business documents into completed business processes through intelligent ingestion, AI-assisted processing, workflow automation, exception review, delivery, archive, and search.

Intelligent Ingestion

PDocs AI is designed to receive documents from the places businesses already use without forcing teams into a single intake method.

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Email intake

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SFTP drops

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Web upload

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API intake

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Scanner batch processing

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Mobile upload

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Partner systems and customer portals

AI Processing

Documents are classified, analyzed, matched, and validated so routine processing can move forward automatically.

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Document classification

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Metadata extraction

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Business object matching

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Validation rules

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Exception detection

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Natural language search support

Workflow Automation

Configurable workflows help automate routing, review, approvals, delivery, retention, and archive policies.

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Document routing

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Approval workflows

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Exception queues

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Delivery automation

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Retention workflows

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Audit history

Enterprise S3 Storage

Original documents, processed versions, OCR content, AI extraction results, delivery packets, and archived records are stored within secure enterprise-grade S3-compatible storage.

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Immutable original documents

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Processed versions

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OCR content

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AI extraction results

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Delivery packets

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Archived records

Review Workspace

Users focus on exceptions that require human judgment instead of manually sorting every document.

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Document viewer

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Page thumbnails

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Split and merge tools

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Redaction review

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Metadata approval

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Exception resolution

Search & Archive

Documents become searchable across metadata, OCR text, workflow history, and archive records.

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Metadata search

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OCR search

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Natural language search

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Archived packets

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Audit trail search

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Retention-based archive

Built for enterprise confidence without exposing unnecessary implementation details.

PDocs AI explains the controls, workflows, deployment options, and governance posture that matter to buyers while keeping sensitive implementation details private.