OpenText Core Capture Services - Steg.ai Integration and Automation

Common Integration Use Cases Between OpenText Core Capture Services and Steg.ai

1. Intelligent document intake with automated image classification and capture

Data flow: Steg.ai ? OpenText Core Capture Services

Steg.ai can analyze incoming scanned images, photos, and mixed-format documents to identify document type, quality, and content category before handing them to OpenText Core Capture Services for extraction. This improves capture accuracy for invoices, forms, and correspondence by routing each item to the right extraction template or workflow.

• Reduces misclassification of poor-quality or mixed document batches
• Improves straight-through processing for high-volume mailroom operations
• Minimizes manual sorting and rework for operations teams

2. Secure digital mailroom processing with content tagging and downstream routing

Data flow: Steg.ai ? OpenText Core Capture Services

In a digital mailroom, Steg.ai can tag incoming documents by sensitivity, department, or content type, then OpenText Core Capture Services can extract key fields and route the documents into the correct business process. For example, HR correspondence, legal notices, and supplier invoices can be separated and processed differently from a single intake stream.

• Supports faster triage of inbound correspondence
• Improves compliance by identifying sensitive content early
• Enables department-specific workflows without manual sorting

3. Invoice and contract image enhancement for better data extraction

Data flow: Steg.ai ? OpenText Core Capture Services

Steg.ai can enrich scanned invoices, purchase orders, and contract pages with image-based classification and content intelligence, helping OpenText Core Capture Services extract fields more reliably from complex layouts. This is especially useful for multi-page supplier documents, low-resolution scans, or documents with stamps, handwritten notes, and embedded logos.

• Improves extraction quality for AP automation and contract intake
• Reduces exception handling caused by unreadable or ambiguous fields
• Speeds up approval cycles by delivering cleaner structured data

4. Sensitive document identification before capture and workflow initiation

Data flow: Steg.ai ? OpenText Core Capture Services

Steg.ai can detect and tag sensitive or restricted content such as personal data, financial records, or confidential correspondence before OpenText Core Capture Services sends the document into downstream workflows. This allows organizations to apply different capture rules, retention policies, or approval paths based on document sensitivity.

• Supports privacy and records management requirements
• Helps prevent accidental routing of restricted documents
• Enables policy-based processing from the point of intake

5. Automated asset enrichment for captured business documents

Data flow: OpenText Core Capture Services ? Steg.ai

After OpenText Core Capture Services extracts document metadata and text, that information can be sent to Steg.ai to improve content classification and tagging. This is useful when captured documents are later stored in a content repository or digital asset platform and need richer labels for search, retrieval, or governance.

• Enhances document discoverability across enterprise repositories
• Creates more consistent metadata for downstream users
• Supports better search and reporting for business teams

6. Quality assurance loop for exception documents and reclassification

Data flow: Bi-directional

OpenText Core Capture Services can send low-confidence or exception documents to Steg.ai for additional image recognition and classification, while Steg.ai can return improved labels or confidence indicators to help OpenText Core Capture Services reprocess the document. This creates a practical exception-handling loop for documents that fail initial capture rules.

• Reduces manual intervention for edge-case documents
• Improves capture success rates over time
• Helps operations teams focus on true exceptions instead of routine cleanup

7. Automated protection and tagging for captured customer onboarding documents

Data flow: OpenText Core Capture Services ? Steg.ai

During customer onboarding, OpenText Core Capture Services can capture application forms, identity documents, and supporting records, then pass them to Steg.ai for tagging and protection classification. This helps teams organize onboarding assets by customer, document type, and sensitivity while applying the right protection controls to personal and regulated information.

• Improves onboarding file organization and audit readiness
• Supports secure handling of identity and compliance documents
• Helps customer operations and compliance teams work from the same source of truth

8. Cross-functional document intelligence for shared services operations

Data flow: Bi-directional

OpenText Core Capture Services can extract structured data from incoming business documents, while Steg.ai can add classification and protection metadata for broader enterprise use. Together, they support shared services teams such as AP, HR, legal, and procurement by turning incoming documents into governed, searchable, and workflow-ready records.

• Improves collaboration across finance, operations, compliance, and records teams
• Creates a more complete document profile for downstream systems
• Supports scalable processing across multiple business functions