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Data flow: Google Document AI ? OpenText Core Signature
Google Document AI extracts key fields from incoming contracts, such as party names, dates, renewal terms, and signature blocks. The extracted data is then used to auto-classify the document and route it into the correct OpenText Core Signature workflow for review and signing. This reduces manual document preparation and speeds up contract turnaround.
Business value: Faster contract processing, fewer data entry errors, and improved legal and procurement efficiency.
Data flow: OpenText Core Signature ? Google Document AI
After a document is signed in OpenText Core Signature, the final signed PDF can be sent to Google Document AI for extraction of signature metadata, approval dates, signer identities, and document content. This supports automated validation, indexing, and downstream archiving in records management or ECM systems.
Business value: Better auditability, easier retrieval, and more reliable records classification.
Data flow: Google Document AI ? OpenText Core Signature
HR teams can use Google Document AI to extract information from onboarding documents such as offer letters, tax forms, and identity documents. The extracted data can populate employee records and trigger the correct signature package in OpenText Core Signature for the new hire and internal approvers. This creates a streamlined onboarding workflow with fewer manual handoffs.
Business value: Shorter onboarding cycles, improved employee experience, and reduced administrative workload.
Data flow: Google Document AI ? OpenText Core Signature
Customer-submitted forms, such as account applications, KYC documents, or service enrollment packets, are processed by Google Document AI to extract customer details and verify completeness. Based on the extracted data, OpenText Core Signature assembles the appropriate signature packet for customer approval and internal compliance review.
Business value: Faster customer activation, fewer incomplete submissions, and stronger compliance control.
Data flow: Google Document AI ? OpenText Core Signature
Accounts payable teams can use Google Document AI to capture invoice data, purchase order references, and approval thresholds from supplier documents. If a signature or approval is required, the invoice is routed through OpenText Core Signature to the correct manager or finance approver. This supports controlled approval workflows for high-value or exception-based invoices.
Business value: Reduced invoice processing time, improved approval accuracy, and better spend governance.
Data flow: OpenText Core Signature ? Google Document AI
Regulatory forms, policy acknowledgements, and compliance attestations signed in OpenText Core Signature can be sent to Google Document AI for content extraction and validation. Compliance teams can automatically check for missing fields, expired dates, or required clauses before storing the documents in the enterprise repository.
Business value: Stronger compliance oversight, faster exception detection, and reduced manual review effort.
Data flow: Bi-directional
Google Document AI can classify incoming documents and extract metadata to determine whether a document requires signature, internal approval, or both. OpenText Core Signature then manages the signing workflow, and once completed, the signed output returns to Google Document AI for final indexing and metadata enrichment. This is useful for enterprise records workflows where documents must be both approved and accurately categorized.
Business value: End-to-end workflow automation, improved records quality, and better cross-department coordination.
Data flow: Google Document AI ? OpenText Core Signature
When Google Document AI detects missing signatures, inconsistent fields, or non-standard document layouts, the document can be flagged and sent to OpenText Core Signature for exception-based review and corrective signing. This is especially useful for legal, procurement, and operations teams handling high volumes of variable document types.
Business value: Better exception management, fewer processing delays, and improved operational control.