OpenText Information Archive - Google Document AI Integration and Automation

Common Integration Use Cases Between OpenText Information Archive and Google Document AI

OpenText Information Archive and Google Document AI complement each other well in enterprise content and records workflows. OpenText Information Archive provides compliant long-term retention, legal hold, and controlled disposition for business records, while Google Document AI extracts structured data from scanned documents, PDFs, and forms using AI. Together, they support digitization, classification, retention, and audit-ready archiving across high-volume document processes.

1. Intelligent capture and compliant archiving of inbound documents

Data flow: Google Document AI to OpenText Information Archive

Incoming invoices, contracts, claims, HR forms, and customer correspondence are processed in Google Document AI to extract key fields such as document type, dates, parties, amounts, and reference numbers. The extracted metadata is then passed to OpenText Information Archive, where the original document and indexed data are stored under the correct retention policy.

• Reduces manual indexing and filing effort
• Improves searchability and retrieval for audit and operations teams
• Ensures documents are archived with the right retention and disposition rules

2. Legacy system decommissioning with document digitization and archival preservation

Data flow: OpenText Information Archive and Google Document AI working together

When retiring a legacy ECM, ERP, or case management system, historical documents can be exported into Google Document AI for OCR and classification. Document AI extracts metadata from scanned or image-based records, which is then loaded into OpenText Information Archive to preserve access, retention, and compliance after the source system is shut down.

• Supports legacy application retirement without losing document accessibility
• Converts unstructured archives into searchable, governed records
• Reduces infrastructure and support costs tied to outdated platforms

3. Automated contract intake, classification, and retention assignment

Data flow: Google Document AI to OpenText Information Archive

Legal and procurement teams can route executed contracts through Google Document AI to identify contract type, effective date, renewal terms, counterparty, and signature status. That metadata is used to archive the contract in OpenText Information Archive with the correct retention schedule, legal hold eligibility, and disposition date.

• Improves contract governance and lifecycle control
• Helps legal teams quickly locate agreements during disputes or audits
• Reduces risk of premature deletion or inconsistent retention handling

4. Accounts payable document processing with audit-ready storage

Data flow: Google Document AI to OpenText Information Archive

Invoices, packing slips, and supporting documents are captured in Google Document AI to extract supplier name, invoice number, PO number, line items, tax amounts, and payment terms. The processed documents and metadata are then archived in OpenText Information Archive to support financial controls, audit requests, and statutory retention requirements.

• Speeds up invoice validation and exception handling
• Creates a complete audit trail for finance and compliance teams
• Supports retention of source documents tied to payment transactions

5. Claims or case file assembly for regulated industries

Data flow: Google Document AI to OpenText Information Archive

In insurance, healthcare, or public sector environments, supporting documents such as claim forms, medical records, correspondence, and evidence files can be processed by Google Document AI to extract case identifiers and document attributes. OpenText Information Archive then stores the documents as a governed case file with retention aligned to regulatory and legal requirements.

• Improves completeness and consistency of case records
• Enables faster retrieval during investigations or appeals
• Supports retention policies based on case type and jurisdiction

6. Records classification for high-volume mailroom and shared services operations

Data flow: Google Document AI to OpenText Information Archive

Physical mail, scanned correspondence, and shared service intake documents are classified by Google Document AI into categories such as HR, legal, customer service, or compliance. The classification results are used to automatically route and archive the content in OpenText Information Archive with the appropriate record type and retention policy.

• Reduces bottlenecks in centralized mailroom operations
• Improves consistency in records handling across departments
• Supports policy-based archiving without manual review of every document

7. Search and retrieval enhancement for archived content

Data flow: OpenText Information Archive to Google Document AI and back to OpenText Information Archive

Archived documents that were originally stored with limited metadata can be sent to Google Document AI for reprocessing when users need better indexing or when older records must be made more searchable. The enriched metadata can then be written back to OpenText Information Archive to improve future retrieval and reporting.

• Enhances access to historical archives without re-creating the source system
• Improves discovery for legal, compliance, and operations teams
• Helps organizations modernize older archives incrementally

These integration patterns are especially valuable where organizations need both intelligent document understanding and strict records governance. Google Document AI improves extraction and classification, while OpenText Information Archive ensures the content remains compliant, searchable, and defensible over the long term.