OpenText Decision Service - Google Document AI Integration and Automation

Common Integration Use Cases Between OpenText Decision Service and Google Document AI

OpenText Decision Service is well suited for rule-based decision automation, policy enforcement, and dynamic business logic within operational workflows. Google Document AI specializes in extracting structured data from unstructured documents such as invoices, claims, contracts, forms, and correspondence. Together, they create a strong pattern for document-driven decisioning, where Document AI captures and classifies content and OpenText Decision Service applies business rules to determine the next action.

1. Invoice validation and payment routing

Data flow: Google Document AI ? OpenText Decision Service

Accounts payable teams can use Google Document AI to extract invoice fields such as vendor name, PO number, line items, tax, and totals. OpenText Decision Service then evaluates the extracted data against approval thresholds, vendor master rules, duplicate invoice checks, and budget limits. Valid invoices can be routed automatically for straight-through processing, while exceptions are sent to finance reviewers.

• Reduces manual invoice review
• Improves payment cycle time
• Enforces consistent approval policy across business units

2. Claims intake and triage

Data flow: Google Document AI ? OpenText Decision Service

In insurance or healthcare operations, Google Document AI can extract key information from claim forms, supporting documents, and correspondence. OpenText Decision Service can then apply rules to determine claim type, priority, eligibility, required documentation, and routing path. Simple claims can be fast-tracked, while incomplete or high-risk claims are escalated to specialist teams.

• Speeds up claim handling
• Improves first-pass accuracy
• Supports consistent triage based on policy rules

3. Contract review and obligation routing

Data flow: Google Document AI ? OpenText Decision Service

Legal and procurement teams can use Google Document AI to extract clauses, dates, renewal terms, termination conditions, and party details from contracts. OpenText Decision Service can evaluate extracted terms against company policy, risk thresholds, and approval matrices. Contracts that meet standard terms can proceed automatically, while non-standard clauses are routed to legal or compliance review.

• Shortens contract review cycles
• Improves policy compliance
• Helps identify risky terms early

4. Customer onboarding and KYC decisioning

Data flow: Google Document AI ? OpenText Decision Service

For banking, fintech, and regulated onboarding processes, Google Document AI can extract identity details from passports, licenses, utility bills, and registration documents. OpenText Decision Service can then apply KYC and onboarding rules such as document completeness, age verification, address validation, risk scoring thresholds, and sanctions review triggers. Low-risk applications can be approved faster, while exceptions are escalated for manual review.

• Improves onboarding turnaround time
• Supports regulatory compliance
• Reduces manual document checking

5. Supplier onboarding and compliance screening

Data flow: Google Document AI ? OpenText Decision Service

Procurement teams can use Google Document AI to capture supplier registration data from tax forms, certificates, insurance documents, and banking details. OpenText Decision Service can assess whether the supplier meets onboarding requirements, such as valid certifications, insurance coverage, tax status, and risk category. Approved suppliers can be activated automatically, while missing or expired documents trigger follow-up tasks.

• Accelerates supplier setup
• Reduces compliance gaps
• Standardizes onboarding decisions across regions

6. Correspondence classification and case routing

Data flow: Google Document AI ? OpenText Decision Service

Customer service or back-office teams often receive large volumes of letters, emails, scanned forms, and supporting documents. Google Document AI can classify document type and extract key entities such as customer ID, issue type, dates, and references. OpenText Decision Service can then determine the correct case queue, priority level, SLA path, and escalation rules based on business policy.

• Improves case routing accuracy
• Reduces handling delays
• Supports SLA-based prioritization

7. Exception handling for document-based workflows

Data flow: Bi-directional

When Google Document AI cannot confidently extract data or detects ambiguous content, OpenText Decision Service can decide whether the item should be sent for human review, reprocessing, or alternate workflow handling. After a reviewer corrects the data, the updated information can be sent back to refine downstream decisions and complete the process. This pattern is useful for high-volume operations where exceptions must be managed efficiently.

• Creates a controlled exception process
• Improves operational resilience
• Supports human-in-the-loop decisioning

8. Policy-driven document approval and retention decisions

Data flow: Google Document AI ? OpenText Decision Service

Organizations can use Google Document AI to extract metadata from incoming documents such as forms, notices, and regulatory submissions. OpenText Decision Service can then determine whether the document requires approval, retention, escalation, or archival based on content type, jurisdiction, sensitivity, and retention policy. This is especially valuable for compliance, records management, and governance workflows.

• Improves records governance
• Enforces retention and approval rules consistently
• Reduces manual classification effort

Overall, the strongest integration pattern is document extraction from Google Document AI followed by rule-based decisioning in OpenText Decision Service. This combination helps enterprises automate document-heavy processes while keeping business rules centralized, auditable, and easy to update.