Production and distributed document acquisition for paper and electronic input.
Convert images to text and recognize document values, identifiers and barcodes.
Identify document types and separate document sets before extraction.
Capture business data from fixed, semi-structured and variable documents.
Review low-confidence values and exceptions with human-in-the-loop verification.
Release validated documents and metadata to downstream systems using rules and AI-assisted capture.
Acquire paper documents through production or distributed scanning stations.
Group pages into controlled batches for consistent capture processing.
Deskew, rotate, clean, separate and prepare scanned pages for recognition.
Ingest PDFs and image files alongside scanner-based input.
Use separators, barcodes or document rules to identify document boundaries.
Track batches and pages from intake through release.
Convert scanned page images into machine-readable and searchable text.
Recognize printed text, structured values, barcodes and document identifiers.
Apply recognition to defined regions when a known document layout is used.
Run OCR across complete pages for searchable text and downstream analysis.
Use recognition confidence to determine whether automated processing can continue.
Use modern AI-assisted capture to improve interpretation of variable documents.
Identify document type before extraction and downstream processing.
Classify by layout, barcode, text, keywords or defined capture rules.
Use recognized content to distinguish invoices, forms, correspondence and other types.
Use confidence thresholds to auto-classify or send uncertain documents for review.
Combine classification with page separation to create complete document units.
Send unclassified or ambiguous documents to a human operator.
Extract names, dates, numbers, IDs and other business data from document content.
Use known document layouts to capture values from fixed locations.
Locate values relative to labels or recognizable text anchors.
Capture repeating rows and structured detail from forms and invoices.
Normalize and transform extracted values before validation or release.
Apply modern AI-assisted capture where layouts and wording vary.
Review extracted values before documents are released to downstream systems.
Route low-confidence fields or exception documents to an operator.
Apply required fields, formats, lookup rules and cross-field checks.
Show the source page beside extracted values for efficient correction.
Hold incomplete, conflicting or unreadable items for controlled resolution.
Use sampling and review steps to confirm capture accuracy.
Send processed documents and metadata to the correct downstream destination.
Complete capture processing and release validated content.
Deliver images, searchable PDFs, extracted metadata and business data to target repositories and applications.
Trigger downstream content or business processes after successful capture and release.
Route content by document type, metadata, confidence, business unit or destination rule.
Direct failed releases and unresolved documents to controlled exception queues.
Combine scanning, OCR, classification, extraction, validation and routing in one capture pipeline.
Process variable documents that do not follow a single fixed template.
Use operator review only where confidence or business rules require it.
Allow high-confidence documents to continue without unnecessary manual intervention.
Use content and context to improve classification and extraction decisions.
Extend traditional Datacap capture with current AI-assisted IDP patterns.
Orchestrate intake, recognition, classification, extraction, validation and release.
Move batches between automated and human work queues based on rules and confidence.
Apply conditional logic to control capture paths and downstream actions.
Call repositories, line-of-business systems and services during capture processing.
Capture processing errors, retries and exception states for operator action.
Reduce repetitive manual indexing while preserving validation and auditability.
Track batches by status, queue, operator and processing stage.
Observe OCR and extraction confidence, exceptions and rework.
See scanning, classification, validation and release activity.
Find failed or held documents requiring attention.
Review page, document and batch volumes for the demonstration environment.
Use process history to understand how a document moved through capture.
Release captured documents and validated metadata into IBM FileNet.
Represent established Datacap capture and release integration patterns.
Exchange captured data with ERP, CRM, case and business applications.
Release processed documents and metadata to governed file destinations.
Use captured values in downstream database-driven processes.
Connect capture workflows to modern APIs and services where appropriate.
Configure capture servers/services, batch and processing profiles, queues, users, licensing, recognition, validation, export and connectivity.
Configure operator roles, permissions, authentication, service access and administrative controls for capture processing.
Configure capture profiles / batch classes, document types, recognition projects, extraction fields, validation rules and export settings.
Manage capture processes, processing steps/modules, queues, connection profiles, unattended services and automation settings.
Review processing logs, batch history, operator actions, administrative changes and security-sensitive events.
Track capture server/service health, recognition engines, processing queues, temporary storage, export connectivity and support readiness.
Separate scanning, recognition, validation, administration and export responsibilities through roles and permissions.
Preserve batch state, processing events, exception history and operator activity for operational traceability.
Use capture logs and batch history to review processing, recognition results, operator validation, export and administrative activity.
Use authentication, role-based access, service credentials and secure integrations appropriate to the deployed capture environment.
Protect sensitive document images and extracted data through controlled access, secure transport and governed downstream delivery.
Combine controlled capture, validation, traceability, security and governed release to support organizational compliance requirements.