Google Document AI - OpenText Core Digital Asset Management Integration and Automation

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

Google Document AI excels at extracting structured data, classifying documents, and understanding content from scanned files, PDFs, and forms. OpenText Core Digital Asset Management is designed to centrally store, organize, govern, and distribute approved digital assets such as images, videos, brand files, and supporting documents. Together, they can streamline content intake, automate metadata enrichment, improve searchability, and support governed asset workflows across teams.

1. Automated Metadata Extraction for Asset Ingestion

Data flow: Google Document AI to OpenText Core Digital Asset Management

When marketing, legal, or operations teams upload documents, Google Document AI can extract key metadata such as document type, dates, names, contract numbers, product references, or project codes. That metadata is then pushed into OpenText Core Digital Asset Management to automatically tag and classify the asset at ingestion.

• Reduces manual cataloging effort for large content libraries
• Improves search accuracy and asset retrieval
• Supports consistent taxonomy and governance across teams

2. OCR and Content Classification for Scanned Brand and Compliance Assets

Data flow: Google Document AI to OpenText Core Digital Asset Management

Organizations often receive scanned brochures, signed approvals, packaging proofs, or compliance documents that need to be stored alongside digital assets. Google Document AI can OCR these files and classify them by document type, then send the extracted text and classification results to OpenText Core Digital Asset Management for indexing and controlled storage.

• Makes scanned content fully searchable
• Speeds up review and retrieval of legacy or paper-based materials
• Helps compliance teams locate approved versions quickly

3. Rights and Usage Information Capture for Media Assets

Data flow: Google Document AI to OpenText Core Digital Asset Management

For organizations managing licensed imagery, talent releases, or usage agreements, Google Document AI can extract expiration dates, usage restrictions, territory rights, and approval terms from supporting documents. OpenText Core Digital Asset Management can store those details as asset metadata and use them to support governance and controlled distribution.

• Reduces risk of using expired or restricted assets
• Improves visibility into licensing and usage constraints
• Supports audit readiness for brand and legal teams

4. Approval Packet Assembly for Creative and Regulatory Workflows

Data flow: Bi-directional

Creative teams can store approved artwork, packaging, and campaign files in OpenText Core Digital Asset Management, while Google Document AI extracts text from supporting approval forms, annotations, or regulatory documents. The extracted data can be used to route assets for review, while approved versions and final supporting documents are returned to OpenText Core Digital Asset Management for centralized retention.

• Creates a more complete approval record
• Improves traceability between final assets and supporting documentation
• Shortens review cycles for regulated industries such as healthcare, finance, and consumer goods

5. Contract and Release Document Linking to Related Digital Assets

Data flow: Google Document AI to OpenText Core Digital Asset Management

Google Document AI can extract key fields from contracts, model releases, vendor agreements, and content licenses. OpenText Core Digital Asset Management can then link those records to the related image, video, or campaign asset so users can see the governing document alongside the media file.

• Improves context for asset users and approvers
• Reduces time spent searching across separate repositories
• Supports legal and procurement oversight

6. Intelligent Search Enrichment for Enterprise Asset Libraries

Data flow: Google Document AI to OpenText Core Digital Asset Management

As assets are ingested, Google Document AI can extract keywords, entities, and document summaries from embedded PDFs, captions, or accompanying documents. OpenText Core Digital Asset Management can use this enriched metadata to improve faceted search, filtering, and recommendation results for marketing, communications, and operations users.

• Helps users find the right asset faster
• Reduces duplicate asset creation and reuse errors
• Improves discoverability across large content repositories

7. Exception Handling for Unstructured Intake from Field or Partner Teams

Data flow: OpenText Core Digital Asset Management to Google Document AI

When external partners or field teams submit mixed content packages containing forms, scans, and supporting documents, OpenText Core Digital Asset Management can store the incoming files and pass the unstructured documents to Google Document AI for extraction and classification. The results can then be written back to the asset record for downstream review and processing.

• Standardizes intake from non-technical contributors
• Reduces manual triage of mixed document packages
• Improves turnaround time for operations and content teams

8. Governance and Audit Trail Enrichment for Approved Assets

Data flow: Bi-directional

Google Document AI can extract approval dates, signatories, and reference numbers from governance documents, while OpenText Core Digital Asset Management maintains the approved asset version, usage history, and distribution controls. Together, they create a stronger audit trail for regulated content and enterprise brand governance.

• Supports compliance audits and internal reviews
• Provides a single view of asset status and supporting evidence
• Helps enforce approved-use policies across departments