OpenText Core Case - Google Document AI Integration and Automation

Common Integration Use Cases Between OpenText Core Case and Google Document AI

OpenText Core Case and Google Document AI complement each other well in document-intensive, case-driven operations. Google Document AI can extract structured data from incoming documents, while OpenText Core Case can use that data to create, route, and manage cases with full visibility across teams.

1. Automated intake of claims, requests, or investigations

Data flow: Google Document AI to OpenText Core Case

When customers, partners, or internal teams submit PDFs, scans, or forms, Google Document AI extracts key fields such as names, dates, policy numbers, invoice amounts, or incident details. OpenText Core Case then creates a new case automatically with the extracted data, attaches the source document, and assigns the case to the correct team.

• Reduces manual data entry at intake
• Speeds up case creation and triage
• Improves accuracy and consistency of case records

2. Invoice or expense exception handling

Data flow: Google Document AI to OpenText Core Case

For invoices, receipts, or expense claims that require review due to missing fields, duplicate charges, or policy violations, Google Document AI extracts line items and header data. OpenText Core Case opens an exception case for finance teams, including the document, extracted values, and exception reason for review and approval.

• Supports faster resolution of payment exceptions
• Creates a clear audit trail for approvals and disputes
• Helps finance teams focus only on exceptions, not routine processing

3. Compliance and regulatory document review

Data flow: Google Document AI to OpenText Core Case

Organizations handling regulatory filings, KYC documents, policy acknowledgments, or audit evidence can use Google Document AI to extract relevant clauses, identifiers, and dates from submitted documents. OpenText Core Case then routes the case to compliance officers for review, approval, or remediation based on the extracted content.

• Improves compliance review turnaround time
• Standardizes handling of regulatory submissions
• Supports traceability for audits and internal controls

4. Customer support case enrichment from attachments

Data flow: Google Document AI to OpenText Core Case

When customers submit support tickets with screenshots, forms, contracts, or service records, Google Document AI extracts the relevant information and passes it into OpenText Core Case. Support agents receive a richer case view with structured data already populated, helping them diagnose issues faster and reduce back-and-forth with the customer.

• Improves first-contact resolution rates
• Reduces time spent reading and interpreting attachments
• Gives agents a more complete case context

5. Contract review and obligation tracking

Data flow: Google Document AI to OpenText Core Case

Legal or procurement teams can use Google Document AI to extract contract metadata such as parties, renewal dates, termination clauses, and service levels. OpenText Core Case can then create a contract review case, assign tasks to legal reviewers, and track approvals, exceptions, and follow-up actions.

• Speeds up contract intake and review
• Reduces missed renewal or obligation dates
• Improves collaboration between legal, procurement, and business owners

6. Claims processing with document verification

Data flow: Google Document AI to OpenText Core Case

In insurance or warranty workflows, claim documents such as receipts, repair estimates, medical forms, or proof of loss can be processed by Google Document AI to extract claim details and verify completeness. OpenText Core Case then manages the claim investigation, routes tasks to adjusters, and tracks supporting evidence and decisions.

• Accelerates claim setup and validation
• Helps identify missing or inconsistent documentation early
• Improves transparency across adjusters, reviewers, and supervisors

7. Bi-directional case status and document request workflow

Data flow: Bi-directional between OpenText Core Case and Google Document AI

OpenText Core Case can trigger requests for additional documents when a case is incomplete, while Google Document AI processes the returned documents and sends extracted data back into the case. This creates a closed-loop workflow for cases that require multiple document submissions, such as onboarding, disputes, or loan applications.

• Keeps cases moving without manual follow-up
• Ensures each new document is immediately usable in the case
• Improves customer and employee experience in document-heavy processes

8. Post-processing and quality control for extracted data

Data flow: Google Document AI to OpenText Core Case, with review updates back to Google Document AI outputs

For high-risk or high-value cases, Google Document AI can extract data from documents and OpenText Core Case can route the case to a human reviewer for validation. If corrections are made, the updated case data can be used to improve downstream processing rules and exception handling.

• Combines automation with human oversight
• Improves data quality for critical decisions
• Supports continuous improvement of document processing workflows

Overall, integrating Google Document AI with OpenText Core Case helps organizations turn unstructured documents into actionable case data, reduce manual handling, and improve speed, accuracy, and accountability across operational workflows.