Automated classification and tagging of documents

Purpose

1.1. Automate the classification and tagging of large volumes of digital documents in investment banks to accelerate data retrieval, streamline compliance checks, support audit trails, and enforce data governance efficiently.
1.2. Create an automated workflow that reads incoming docs (emails, PDFs, contracts), accurately assigns categories/tags, enables automatable auditing, and provides real-time metadata for enhanced security and rapid access.

Trigger Conditions

2.1. Automation initiates on new document upload or receipt in storage repositories, DMS, or email inboxes.
2.2. Automatedly triggers on scheduled scanning of document folders, or when manual tagging is flagged as incomplete, when ML model confidence is below threshold, or when periodic compliance audits require updated tags.

Platform variants

3.1. Box
• Feature/Setting: Automated folder monitoring; configure Event triggers and Box Skills for document classification workflows.
3.2. Microsoft SharePoint
• Feature/Setting: Automate metadata assignment via Power Automate integration APIs and Triggered Flows.
3.3. IBM FileNet Content Manager
• Feature/Setting: Content Classification Service API automates tagging pipelines on new document ingestion events.
3.4. M-Files
• Feature/Setting: Metadata auto-classification settings; configure Intelligent Metadata Layer with trigger actions.
3.5. OpenText Content Suite
• Feature/Setting: Automated Classification Engine; set rules-based or AI-based auto-categorization via REST API.
3.6. Google Drive
• Feature/Setting: Apps Script or Drive API with Cloud Vision and NLP classifies uploaded docs automatically.
3.7. Dropbox Business
• Feature/Setting: Content event triggers via API and automated tagging using Dropbox Extensions.
3.8. Salesforce Files
• Feature/Setting: Flow Builder automation for on-upload document categorizing using Apex triggers.
3.9. Docuware
• Feature/Setting: Intelligent Indexing API for automated classification and workflow rule setup.
3.10. Alfresco
• Feature/Setting: Alfresco Rules and Smart Folders for auto-tagging documents via REST API configurations.
3.11. Egnyte
• Feature/Setting: Automation engine for event-based classification, secure tagging via Smart Classification APIs.
3.12. Laserfiche
• Feature/Setting: Workflow Designer; configure On Entry triggers for metadata automation rules.
3.13. SAP Document Management
• Feature/Setting: SAP Intelligent RPA bots automate tagging with DMS API events.
3.14. NetDocuments
• Feature/Setting: ndThread automation for document classification using custom metadata APIs.
3.15. ElasticSearch
• Feature/Setting: Ingest Node Pipelines for auto-tagging via machine learning inference processors.
3.16. Hyland OnBase
• Feature/Setting: Automated Document Import Processor with AI-based classification workflows.
3.17. Iron Mountain InSight
• Feature/Setting: Automated document tagging workflows configurable in UI with webhooks for incoming data.
3.18. KnowledgeLake
• Feature/Setting: Intelligent Capture automation and tagging by cloud workflow rule triggers.
3.19. Smartsheet
• Feature/Setting: Automated workflows for document intake and tagging with integrations via Bridge connectors.
3.20. Zoho WorkDrive
• Feature/Setting: Automated tagging using WorkDrive API and Zoho Flow automation.
3.21. Google Cloud Document AI
• Feature/Setting: Configure Document AI sync; automate tagging and classification via API processDocument method.
3.22. Amazon Textract
• Feature/Setting: Detection and automated tagging pipeline using StartDocumentAnalysis API trigger.
3.23. Azure Form Recognizer
• Feature/Setting: Automated classify_and_extract workflow using Analyze API with triggers based on storage input.
3.24. PandaDoc
• Feature/Setting: Workflow Automation rules for on-upload document classification and tagging API.

Benefits

4.1. Accelerates finding critical investment banking docs by automating categorization for search and compliance.
4.2. Ensures regulatory and audit-readiness by automating consistent and traceable tag application on confidential documents.
4.3. Reduces manual effort by automating repetitive classification and enabling automatable flows in document operations.
4.4. Improves security by associating automated tags for access rights and sensitive data detection.
4.5. Enables scalable automation as document volumes grow, supporting the automating of all audit and records management tasks.