OpenText Core Content - Metadata - Azure AI Document Intelligence Integration and Automation

Common Integration Use Cases Between OpenText Core Content - Metadata and Azure AI Document Intelligence

1. Automated invoice capture with governed metadata classification

Data flow: Azure AI Document Intelligence ? OpenText Core Content - Metadata

Accounts payable teams can use Azure AI Document Intelligence to extract invoice fields such as vendor name, invoice number, amount, tax, and due date. The extracted data is then mapped into OpenText Core Content - Metadata fields with validation rules and controlled vocabularies to ensure consistent indexing and classification. This improves invoice searchability, supports retention policies, and reduces manual data entry errors.

Business value: Faster invoice processing, improved compliance, and better visibility into spend and payment status.

2. Contract intake and metadata enrichment for legal and procurement teams

Data flow: Azure AI Document Intelligence ? OpenText Core Content - Metadata

When contracts are uploaded into OpenText Core Content, Azure AI Document Intelligence can extract key terms such as effective date, renewal date, counterparty, jurisdiction, and contract type. OpenText metadata rules can then enforce standardized values and required fields before the document is published or routed for approval. This creates a reliable contract repository that supports obligation tracking and renewal management.

Business value: Better contract governance, reduced missed renewals, and improved legal and procurement oversight.

3. Supplier onboarding document processing with metadata-driven workflow routing

Data flow: Azure AI Document Intelligence ? OpenText Core Content - Metadata

Procurement teams often receive tax forms, bank letters, insurance certificates, and registration documents during supplier onboarding. Azure AI Document Intelligence can extract the relevant data from these documents and populate OpenText metadata fields such as supplier category, region, risk tier, and compliance status. Based on the metadata, content can be routed to the correct approval workflow or escalated for exception handling.

Business value: Shorter onboarding cycles, stronger supplier compliance, and less manual coordination across procurement, finance, and legal.

4. Claims or case file indexing for insurance and regulated operations

Data flow: Azure AI Document Intelligence ? OpenText Core Content - Metadata

In insurance, healthcare, and other regulated environments, case files often include forms, supporting evidence, and correspondence. Azure AI Document Intelligence can extract claim numbers, patient or policy identifiers, incident dates, and document types, then OpenText Core Content - Metadata can apply consistent classification and validation. This makes it easier to assemble complete case files and support downstream audits or reviews.

Business value: Faster case handling, improved audit readiness, and more accurate file organization.

5. Metadata validation for incoming document repositories

Data flow: OpenText Core Content - Metadata ? Azure AI Document Intelligence ? OpenText Core Content - Metadata

Organizations can use OpenText metadata definitions to determine what information must be captured for each document class, such as customer ID, region, document category, or business unit. If a document arrives with incomplete or inconsistent metadata, Azure AI Document Intelligence can extract missing values from the document content. The corrected metadata is then written back to OpenText to complete the record and maintain governance standards.

Business value: Higher metadata quality, fewer incomplete records, and stronger repository governance.

6. Automated classification of incoming mail and scanned correspondence

Data flow: Azure AI Document Intelligence ? OpenText Core Content - Metadata

Shared services teams can process scanned mail, customer letters, and inbound forms through Azure AI Document Intelligence to identify document type and extract key attributes. OpenText Core Content - Metadata can then assign the correct category, business owner, and retention label. This enables automated routing to claims, HR, finance, or customer service teams without manual sorting.

Business value: Reduced mailroom effort, faster response times, and improved operational consistency.

7. Compliance evidence management and audit file preparation

Data flow: Azure AI Document Intelligence ? OpenText Core Content - Metadata

Compliance teams can use Azure AI Document Intelligence to extract evidence details from certificates, attestations, inspection reports, and signed forms. OpenText Core Content - Metadata can then enforce required classification fields such as control domain, audit period, owner, and evidence status. This creates a structured evidence library that simplifies audit preparation and recurring compliance reviews.

Business value: Less time spent assembling audit packs, improved traceability, and stronger control over regulated content.

8. Enriched content analytics for operational reporting

Data flow: Azure AI Document Intelligence ? OpenText Core Content - Metadata

Business teams can extract structured data from high-volume document sets and store it in OpenText metadata fields for reporting and analysis. For example, extracted fields from purchase orders, delivery notes, or service forms can be standardized across repositories to support dashboards on processing time, document volume, exception rates, and supplier performance. This helps leaders make decisions based on content-derived operational data rather than manual spreadsheets.

Business value: Better reporting accuracy, improved process visibility, and stronger decision support across departments.