OpenText Active Community - Trading Grid - Google Document AI Integration and Automation

Common Integration Use Cases Between OpenText Active Community - Trading Grid and Google Document AI

OpenText Active Community - Trading Grid is designed to support collaboration across trading partners, while Google Document AI specializes in extracting structured data from unstructured documents such as invoices, purchase orders, bills of lading, claims, and forms. Together, they can streamline partner communication, reduce manual document handling, and improve exception resolution across B2B workflows.

1. Automated extraction of partner-submitted documents into Trading Grid workflows

Data flow: Google Document AI to OpenText Active Community - Trading Grid

When suppliers, carriers, or customers upload documents such as invoices, packing slips, or shipping notices into the community, Google Document AI can extract key fields like document number, dates, line items, totals, and reference IDs. The extracted data can then be posted into Trading Grid collaboration threads or case records for review and approval.

• Reduces manual data entry and document indexing
• Speeds up validation of partner-submitted paperwork
• Improves accuracy in downstream B2B transaction processing

2. Exception management for mismatched invoices and purchase orders

Data flow: Bi-directional

Google Document AI can extract invoice and PO details, then Trading Grid can route mismatches to the appropriate trading partner community for resolution. Buyers and suppliers can collaborate in the shared environment to resolve quantity, price, tax, or reference discrepancies using the original documents and extracted data.

• Accelerates dispute resolution between partners
• Creates a transparent audit trail of issue handling
• Reduces accounts payable and procurement cycle delays

3. Document classification and routing for partner support cases

Data flow: Google Document AI to OpenText Active Community - Trading Grid

Incoming documents from partners can be classified by type, such as customs forms, certificates of origin, compliance declarations, or delivery receipts. Google Document AI identifies the document type and key metadata, then Trading Grid automatically routes the item to the correct internal team or partner group for action.

• Improves first-time routing accuracy
• Shortens response times for partner inquiries
• Supports high-volume shared service operations

4. Proof of delivery and shipment document validation

Data flow: Google Document AI to OpenText Active Community - Trading Grid

Logistics partners can submit proof of delivery, signed receipts, and freight documents into Trading Grid. Google Document AI extracts shipment identifiers, delivery dates, signatures, and exception notes, allowing operations teams to validate delivery completion and identify unresolved claims faster.

• Supports faster freight reconciliation
• Improves visibility into delivery exceptions
• Helps reduce chargebacks and payment delays

5. Compliance document review and partner onboarding

Data flow: Bi-directional

During partner onboarding or periodic compliance reviews, trading partners can upload tax forms, insurance certificates, certifications, and regulatory documents into the community. Google Document AI extracts the required fields, while Trading Grid manages review tasks, missing-document follow-up, and approval collaboration across internal compliance, legal, and partner management teams.

• Standardizes onboarding and compliance checks
• Reduces manual review effort
• Improves governance across the partner ecosystem

6. Automated case creation from document exceptions

Data flow: Google Document AI to OpenText Active Community - Trading Grid

If Google Document AI detects missing fields, low-confidence extraction, or inconsistent values in a submitted document, Trading Grid can automatically create an exception case in the relevant community. The case can include the original document, extracted values, and exception reason so partner teams can resolve the issue collaboratively.

• Ensures exceptions are handled consistently
• Reduces the risk of processing incomplete documents
• Improves operational control in high-volume environments

7. Shared document intelligence for partner performance monitoring

Data flow: Google Document AI to OpenText Active Community - Trading Grid

Document AI can extract operational metrics from partner documents such as turnaround times, shipment dates, invoice receipt dates, and compliance expiration dates. Trading Grid can use this information to support partner scorecards, issue tracking, and collaborative performance reviews.

• Provides measurable insight into partner responsiveness
• Supports data-driven supplier and carrier management
• Helps identify recurring process bottlenecks

These integrations are especially valuable for organizations managing complex B2B ecosystems where document-heavy processes, partner collaboration, and exception handling must work together efficiently.