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.

Email intake

SFTP drops

Web upload

API intake

Scanner batch processing

Mobile upload

Partner systems and customer portals

AI Processing

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

Document classification

Metadata extraction

Business object matching

Validation rules

Exception detection

Natural language search support

Workflow Automation

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

Document routing

Approval workflows

Exception queues

Delivery automation

Retention workflows

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.

Immutable original documents

Processed versions

OCR content

AI extraction results

Delivery packets

Archived records

Review Workspace

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

Document viewer

Page thumbnails

Split and merge tools

Redaction review

Metadata approval

Exception resolution

Search & Archive

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

Metadata search

OCR search

Natural language search

Archived packets

Audit trail search

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.