OpenText Information Archive - Azure AI Document Intelligence Integration and Automation

Common Integration Use Cases Between OpenText Information Archive and Azure AI Document Intelligence

1. Automated ingestion of scanned legacy records into compliant archive

Data flow: Azure AI Document Intelligence ? OpenText Information Archive

Organizations decommissioning paper-heavy or legacy capture systems can use Azure AI Document Intelligence to extract key metadata from scanned contracts, claims, invoices, or correspondence before storing the records in OpenText Information Archive. The extracted fields such as document type, customer ID, case number, and retention category can be used to classify and index content correctly at the point of archive.

Business value: Reduces manual indexing effort, improves searchability, and ensures archived records are retained under the correct policy from day one.

2. Legacy system retirement with intelligent document classification

Data flow: Azure AI Document Intelligence ? OpenText Information Archive

When retiring an old ECM, ERP, or line-of-business system, organizations can export historical documents and run them through Azure AI Document Intelligence to identify document types and extract metadata needed for compliant archiving. OpenText Information Archive then becomes the long-term repository for the decommissioned content, preserving access without keeping the source system online.

Business value: Lowers infrastructure and support costs, accelerates application retirement, and preserves audit-ready access to historical records.

3. Invoice and accounts payable record archiving with enriched metadata

Data flow: Azure AI Document Intelligence ? OpenText Information Archive

Accounts payable teams can process incoming invoices with Azure AI Document Intelligence to capture invoice number, vendor, amount, PO reference, and due date. Once validated, the invoice image and extracted metadata are archived in OpenText Information Archive for retention, audit support, and future retrieval during disputes or compliance reviews.

Business value: Improves AP efficiency, supports financial controls, and creates a reliable archive for audit and tax requirements.

4. Contract repository creation with searchable clause and metadata extraction

Data flow: Azure AI Document Intelligence ? OpenText Information Archive

Legal and procurement teams can use Azure AI Document Intelligence to extract contract metadata such as counterparty, effective date, renewal date, jurisdiction, and contract type from signed agreements. The documents are then stored in OpenText Information Archive with retention rules aligned to legal and regulatory obligations.

Business value: Enables faster contract retrieval, supports renewal tracking, and reduces risk from missed retention or disposal events.

5. Compliance evidence archiving from operational document streams

Data flow: Azure AI Document Intelligence ? OpenText Information Archive

In regulated industries, operational documents such as inspection reports, onboarding forms, shipping records, or quality certificates can be processed by Azure AI Document Intelligence to extract evidence fields and then archived in OpenText Information Archive. This creates a defensible record set for audits, investigations, and regulatory submissions.

Business value: Strengthens compliance posture, shortens audit response times, and reduces the risk of missing or misfiled evidence.

6. Archival search enhancement using extracted metadata from unstructured documents

Data flow: Azure AI Document Intelligence ? OpenText Information Archive

For large archives containing unstructured documents, Azure AI Document Intelligence can be used to enrich records with additional metadata after ingestion. For example, archived correspondence or claims files can be reprocessed to extract names, dates, policy numbers, or case references, improving indexing and retrieval inside OpenText Information Archive.

Business value: Makes archived content easier to find and reuse, reducing time spent by legal, customer service, and records teams searching for records.

7. Exception handling and reprocessing for incomplete archived documents

Data flow: OpenText Information Archive ? Azure AI Document Intelligence ? OpenText Information Archive

When archived documents are missing metadata or were originally captured with poor quality, records teams can send selected items from OpenText Information Archive to Azure AI Document Intelligence for re-extraction. Corrected metadata is then written back to the archive to improve record quality and retention accuracy.

Business value: Improves archive integrity over time, reduces manual remediation, and supports better governance of historical records.

8. Analytics-ready archival of business documents after extraction

Data flow: Azure AI Document Intelligence ? OpenText Information Archive

Business units can process high-volume documents such as claims, purchase orders, or onboarding packets with Azure AI Document Intelligence, then archive both the original documents and extracted metadata in OpenText Information Archive. The archive becomes the system of record for compliance, while the structured metadata can also support downstream reporting and operational analysis.

Business value: Combines compliant retention with better visibility into document-driven processes, helping teams identify bottlenecks and trends.