OpenText Core Experience Insights - Google Document AI Integration and Automation

Common Integration Use Cases Between OpenText Core Experience Insights and Google Document AI

1. Measure document processing adoption and automation impact

Data flow: Google Document AI ? OpenText Core Experience Insights

Use Google Document AI to extract data from invoices, claims, contracts, or forms, then send processing metrics and user interaction events into OpenText Core Experience Insights. Business teams can track how often documents are processed automatically versus manually reviewed, where users intervene, and which document types create the most friction. This helps operations leaders quantify automation ROI and identify process bottlenecks.

2. Improve document review workflows for exception handling

Data flow: Google Document AI ? OpenText Core Experience Insights ? Google Document AI

When Document AI flags low-confidence fields or exceptions, OpenText Core Experience Insights can capture reviewer actions such as corrections, rejections, and rework patterns. Those insights can then be used to refine validation rules, routing logic, and document templates in Google Document AI. This is valuable for finance, procurement, and shared services teams that need to reduce manual reprocessing and improve straight-through processing rates.

3. Analyze employee self-service document journeys

Data flow: OpenText Core Experience Insights ? Google Document AI

OpenText Core Experience Insights can reveal how employees interact with document-heavy self-service portals, such as HR onboarding, benefits enrollment, or policy request workflows. Those usage patterns can guide where Google Document AI should be applied to extract data from uploaded forms, IDs, or supporting documents. The result is a smoother employee experience with fewer drop-offs and faster case resolution for HR and service desk teams.

4. Optimize customer onboarding and KYC document capture

Data flow: OpenText Core Experience Insights ? Google Document AI ? OpenText Core Experience Insights

In customer onboarding journeys, OpenText Core Experience Insights can identify where applicants abandon forms, upload incomplete documents, or spend excessive time on document steps. Google Document AI can then extract data from identity documents, proof of address, and application forms to reduce manual entry. Feedback from processing outcomes can be sent back to OpenText Core Experience Insights to monitor completion rates, error rates, and conversion improvements across onboarding channels.

5. Track content quality issues that affect extraction accuracy

Data flow: OpenText Core Experience Insights ? Google Document AI

OpenText Core Experience Insights can surface patterns such as repeated document uploads, high correction rates, or frequent user retries in specific business processes. These signals often indicate poor source document quality, inconsistent templates, or confusing capture steps. Feeding these insights into Google Document AI implementation teams helps them adjust classification models, improve document templates, and prioritize the document types that need the most tuning.

6. Support continuous improvement for claims and case management

Data flow: Google Document AI ? OpenText Core Experience Insights

In insurance claims or service case management, Google Document AI can extract key fields from claim forms, supporting evidence, and correspondence. OpenText Core Experience Insights can then measure how claims handlers use the extracted information, where they spend time, and which screens or document views drive the most rework. Claims operations can use this to streamline case handling, reduce handling time, and improve handler productivity.

7. Build governance dashboards for document-centric transformation programs

Data flow: Bi-directional

Enterprises running document automation programs can combine Document AI extraction results with OpenText Core Experience Insights usage analytics to create governance dashboards for business and IT stakeholders. These dashboards can show adoption by department, exception rates by document type, manual override frequency, and process cycle time trends. This supports program governance, prioritization of automation backlog items, and better alignment between business outcomes and technical performance.