Azure - OpenText Core Digital Asset Management Integration and Automation

Common Integration Use Cases Between Azure AI Document Intelligence and OpenText Core Digital Asset Management

1. Auto-tagging and indexing of document-derived assets

Data flow: Azure AI Document Intelligence → OpenText Core Digital Asset Management

When scanned contracts, product sheets, labels, or compliance documents are ingested into Azure AI Document Intelligence, key metadata such as document type, customer name, project ID, expiry date, or region can be extracted and passed to OpenText Core Digital Asset Management. This enables automatic tagging, classification, and folder assignment of related digital assets.

Business value: Reduces manual cataloging effort, improves searchability, and ensures assets are organized consistently across teams.

2. Centralized management of approved document versions and supporting assets

Data flow: Bi-directional

Azure AI Document Intelligence can extract version numbers, approval dates, and reference identifiers from source documents such as packaging specs, regulatory forms, or marketing approvals. OpenText Core Digital Asset Management can store the approved visual or reference assets linked to those extracted records. Updates in the DAM can be used to validate whether a document version is current, while extracted metadata can trigger replacement or archival workflows.

Business value: Helps teams avoid using outdated assets and supports version control across regulated or brand-sensitive content.

3. Invoice and receipt attachment management for finance and procurement

Data flow: Azure AI Document Intelligence → OpenText Core Digital Asset Management

Invoices, receipts, and supporting documents processed by Azure AI Document Intelligence can have supplier names, PO numbers, amounts, and dates extracted and then stored alongside related images, signed approvals, or proof-of-delivery files in OpenText Core Digital Asset Management. Finance and procurement teams can retrieve all supporting materials from one governed repository.

Business value: Improves audit readiness, speeds up dispute resolution, and reduces time spent searching for supporting documentation.

4. Compliance evidence packaging for audits and regulatory reviews

Data flow: Azure AI Document Intelligence → OpenText Core Digital Asset Management

Organizations can use Azure AI Document Intelligence to extract control IDs, policy references, dates, and sign-off details from compliance documents, then store the associated evidence files in OpenText Core Digital Asset Management. This creates a structured evidence package for audits, inspections, and internal control reviews.

Business value: Simplifies audit preparation, improves traceability, and supports consistent evidence retention across departments.

5. Product content enrichment for marketing and eCommerce teams

Data flow: Azure AI Document Intelligence → OpenText Core Digital Asset Management

Product specification sheets, regulatory inserts, and packaging documents can be processed by Azure AI Document Intelligence to extract product codes, dimensions, ingredients, warnings, and market-specific attributes. These fields can then enrich asset records in OpenText Core Digital Asset Management, making it easier for marketing, merchandising, and eCommerce teams to find and reuse the correct approved content.

Business value: Accelerates product launches, improves content accuracy, and reduces the risk of publishing incomplete or non-compliant materials.

6. Contract and rights-document linkage for media and brand assets

Data flow: Azure AI Document Intelligence → OpenText Core Digital Asset Management

Rights agreements, talent releases, licensing contracts, and usage terms can be analyzed by Azure AI Document Intelligence to extract expiration dates, usage restrictions, territories, and permitted channels. OpenText Core Digital Asset Management can then associate those rights details with the relevant images, videos, or campaign assets to control access and usage.

Business value: Prevents unauthorized asset use, supports rights compliance, and reduces legal review effort.

7. Search and retrieval of source documents from asset records

Data flow: OpenText Core Digital Asset Management → Azure AI Document Intelligence

When users search for an asset in OpenText Core Digital Asset Management, the system can pass the linked source document or scanned file to Azure AI Document Intelligence for deeper extraction of embedded text and fields. This is useful when a DAM record contains a visual asset plus a related document that needs to be read, validated, or summarized before reuse.

Business value: Improves discovery of information hidden in scanned or image-based documents and supports faster decision-making.

8. Automated onboarding of document-heavy campaign or project packages

Data flow: Bi-directional

For new campaigns, construction projects, or customer onboarding packages, Azure AI Document Intelligence can extract structured data from intake forms, approvals, and reference documents, while OpenText Core Digital Asset Management stores the associated creative files, reference images, and final deliverables. The extracted metadata can drive folder creation, asset classification, and workflow routing in the DAM.

Business value: Streamlines cross-team onboarding, reduces manual setup, and creates a consistent project record from day one.