OCR (Optical Character Recognition) for incoming records

Purpose

1.1. Automate extraction of data from physical or digital records using advanced OCR to enable automated indexing, archiving, and record retrieval in professional records storage facilities.
1.2. Automating data capture to reduce manual input errors, accelerate information flow, and ensure automated compliance for document and records management.
1.3. Provide an automatable, scalable solution for handling high document volumes in archival storage and warehousing environments.

Trigger Conditions

2.1. Arrival of new physical records to be digitally archived.
2.2. Upload or scanning of images, PDFs, or handwritten records into the system.
2.3. Scheduled automated batch processing intervals for existing backlog documents.
2.4. Email receipt with attachments requiring automated OCR processing.
2.5. Detection of new documents in monitored cloud storage locations.

Platform Variants

3.1. Microsoft Power Automate
• Feature/Setting: AI Builder - OCR; configure to extract data from incoming scanned documents automatically.
3.2. Google Cloud Vision API
• Feature/Setting: Text Detection function; automatedly process uploaded images/PDFs for string extraction.
3.3. Amazon Textract
• Feature/Setting: AnalyzeDocument; automate content extraction when documents land in S3 bucket.
3.4. Adobe PDF Services
• Feature/Setting: Extract API for automating text and table recognition from PDFs.
3.5. ABBYY FlexiCapture
• Feature/Setting: Automated batch OCR for invoices, records, and forms on upload trigger.
3.6. Kofax Capture
• Feature/Setting: Automated document classification and data extraction with rule-based triggers.
3.7. Tesseract OCR
• Feature/Setting: Command-line/REST API calls for automated OCR on new files in processing directory.
3.8. Docparser
• Feature/Setting: Automated parsing rules triggered by new file arrival via email or integrated cloud storage.
3.9. Hypatos
• Feature/Setting: REST API for end-to-end automated document OCR and data capture.
3.10. IBM Watson Visual Recognition
• Feature/Setting: Document OCR workflow driven by file creation in connected storage.
3.11. Rossum
• Feature/Setting: Automated extraction queue triggered by email or cloud upload.
3.12. UiPath
• Feature/Setting: OCR Activities; automate document batch extraction from folders.
3.13. Parascript
• Feature/Setting: Smart Automation OCR API for automated transcription of handwritten and machine print records.
3.14. Ephesoft Transact
• Feature/Setting: Automated classification and extraction on new document batch import.
3.15. SimpleOCR API
• Feature/Setting: Instant OCR processing triggered by HTTP request or storage change.
3.16. Datadog OCR Monitor
• Feature/Setting: Automated audit log and alerting for all OCR automated activities.
3.17. Foxit PDF SDK
• Feature/Setting: OCR feature automated via SDK in incoming document handler.
3.18. Azure Cognitive Services
• Feature/Setting: Read API for real-time automated OCR on uploaded content in Blob storage.
3.19. PandaDoc
• Feature/Setting: Document OCR automator functionality for contracts and archival records.
3.20. Zoho WorkDrive OCR
• Feature/Setting: Auto OCR on newly added files in storage folders.
3.21. Veryfi API
• Feature/Setting: Receipt and document OCR via automated REST call on scan detection.
3.22. Notion Automation
• Feature/Setting: OCR automatic extractor triggered by new file blocks.

Benefits

4.1. Automatedly boosts productivity and accuracy by removing manual transcription.
4.2. Streamlines document indexing and automates searching within massive archives.
4.3. Supports compliance by automating audit trails and secure data capture.
4.4. Automates time-sensitive document ingestion and retrieval.
4.5. Reduces costs associated with manual data entry in storage & warehousing contexts.
4.6. Enables fast automation of downstream workflows based on extracted data.