Azure Computer Vision - OpenText Content Metadata Service - Dictionary Integration and Automation

Common Integration Use Cases Between Azure Computer Vision and OpenText Content Metadata Service - Dictionary

1. Automated metadata tagging for images and scanned documents

Flow: Azure Computer Vision to OpenText Content Metadata Service - Dictionary

Azure Computer Vision extracts text, detects objects, and identifies visual attributes from images, scans, and PDFs. The extracted insights are mapped to governed metadata fields defined in OpenText Content Metadata Service - Dictionary, ensuring consistent classification across OpenText repositories.

• Business value: reduces manual indexing effort and improves metadata accuracy.
• Operational benefit: standardizes tags such as document type, department, product line, and region.
• Typical users: records management, content operations, and shared services teams.

2. Controlled vocabulary enforcement for AI-generated tags

Flow: Bi-directional

Azure Computer Vision can generate candidate tags from visual content, while OpenText Content Metadata Service - Dictionary validates those tags against approved values and metadata rules. If a tag does not match the controlled vocabulary, it can be normalized or routed for review.

• Business value: prevents inconsistent or duplicate metadata across content systems.
• Operational benefit: improves search precision and reporting consistency.
• Typical users: information governance, taxonomy, and content governance teams.

3. OCR-based document classification and metadata enrichment

Flow: Azure Computer Vision to OpenText Content Metadata Service - Dictionary

Azure Computer Vision performs OCR on invoices, contracts, forms, and correspondence to extract key text such as names, dates, reference numbers, and document titles. These values are then written into OpenText metadata fields defined in the dictionary for downstream routing and retention handling.

• Business value: accelerates document intake and improves retrieval.
• Operational benefit: supports automated filing, case creation, and compliance workflows.
• Typical users: AP, legal operations, customer service, and mailroom teams.

4. Image-based content moderation with governed classification

Flow: Azure Computer Vision to OpenText Content Metadata Service - Dictionary

For marketing assets, user-generated content, or brand portals, Azure Computer Vision detects unsafe, off-brand, or restricted visual content. The moderation outcome is stored in OpenText using standardized metadata values such as approved, restricted, pending review, or rejected.

• Business value: reduces brand and compliance risk.
• Operational benefit: enables faster review queues and audit-ready status tracking.
• Typical users: marketing operations, legal review, and digital asset management teams.

5. Product and asset recognition for digital asset management

Flow: Azure Computer Vision to OpenText Content Metadata Service - Dictionary

Azure Computer Vision identifies products, packaging, logos, and scene attributes in images used for e-commerce or DAM. OpenText Content Metadata Service - Dictionary stores these recognized attributes using standardized product and campaign metadata, making assets easier to search and reuse.

• Business value: improves asset discoverability and reuse across channels.
• Operational benefit: supports faster catalog updates and campaign production.
• Typical users: e-commerce, merchandising, and creative operations teams.

6. Accessibility metadata generation for published content

Flow: Azure Computer Vision to OpenText Content Metadata Service - Dictionary

Azure Computer Vision generates descriptive text for images and identifies key visual elements that can be used as alt text or accessibility descriptors. OpenText Content Metadata Service - Dictionary governs the approved metadata fields for accessibility attributes, ensuring consistent publishing standards.

• Business value: supports accessibility compliance and improves user experience.
• Operational benefit: streamlines content publishing for web and intranet teams.
• Typical users: digital publishing, web content, and compliance teams.

7. Metadata governance for multi-repository content harmonization

Flow: OpenText Content Metadata Service - Dictionary to Azure Computer Vision and back

OpenText Content Metadata Service - Dictionary provides the master metadata model for multiple repositories. Azure Computer Vision enriches incoming assets with visual intelligence, and the resulting metadata is normalized back into the shared dictionary so content from different sources follows the same classification structure.

• Business value: creates a single metadata standard across business units and repositories.
• Operational benefit: improves interoperability between DAM, ECM, and archive platforms.
• Typical users: enterprise architecture, master data, and content governance teams.

8. Exception handling and human review workflow for low-confidence extraction

Flow: Azure Computer Vision to OpenText Content Metadata Service - Dictionary

When Azure Computer Vision returns low-confidence OCR or recognition results, the content can be flagged in OpenText with a governed status such as needs review or exception. The dictionary ensures reviewers use approved metadata values when correcting or completing the record.

• Business value: improves data quality without slowing automation.
• Operational benefit: creates a controlled review process for ambiguous content.
• Typical users: content operations, quality assurance, and business process teams.