Prodigy - OpenText Active Documents Trading Grid Integration and Automation

Common Integration Use Cases Between Prodigy and OpenText Active Documents Trading Grid

Prodigy and OpenText Active Documents Trading Grid serve very different but complementary roles. Prodigy helps teams create high-quality labeled datasets for machine learning, while OpenText Active Documents Trading Grid manages secure, auditable exchange of business documents with trading partners. Together, they can support intelligent document processing, automated classification, and human-in-the-loop workflows across supply chain and enterprise operations.

• 1. Train document classification models using trading partner documents

  Data flow: OpenText Active Documents Trading Grid to Prodigy

  Inbound invoices, purchase orders, shipping notices, and other partner documents can be exported from OpenText Active Documents Trading Grid into Prodigy for annotation. Data teams can label document types, key fields, exceptions, and compliance attributes to build models that automatically classify and route future documents.

  Business value: Reduces manual document sorting, improves processing speed, and creates a reusable training set for intelligent document automation.

• 2. Build extraction models for invoice and order data capture

  Data flow: OpenText Active Documents Trading Grid to Prodigy to downstream OCR or IDP systems

  Business documents exchanged through OpenText Active Documents Trading Grid can be sampled and annotated in Prodigy to train models that extract fields such as invoice number, PO number, line items, ship dates, and tax amounts. The resulting models can then support automated data capture in accounts payable, procurement, and logistics workflows.

  Business value: Lowers manual keying effort, improves accuracy of downstream processing, and accelerates transaction handling.

• 3. Create exception handling models for non standard partner documents

  Data flow: OpenText Active Documents Trading Grid to Prodigy and back to workflow systems

  When trading partners send documents in varying formats or with missing fields, those exceptions can be routed from OpenText Active Documents Trading Grid into Prodigy for labeling. Teams can annotate the exception patterns and train models to detect anomalies, incomplete submissions, or non compliant document structures before they enter core business systems.

  Business value: Improves compliance, reduces downstream rework, and helps operations teams focus on true exceptions instead of routine transactions.

• 4. Support active learning for high volume document processing

  Data flow: OpenText Active Documents Trading Grid to Prodigy, then model scores back to workflow

  As new documents arrive through OpenText Active Documents Trading Grid, a machine learning model trained in Prodigy can score them for confidence and uncertainty. Low confidence documents can be sent back to Prodigy for additional labeling, allowing the model to continuously improve on the most difficult cases.

  Business value: Maximizes labeling efficiency, improves model performance over time, and reduces the cost of maintaining document automation at scale.

• 5. Automate partner specific document routing and validation

  Data flow: Bi directional

  OpenText Active Documents Trading Grid can provide partner metadata, document type, and transaction context to Prodigy for training routing and validation models. In return, Prodigy trained models can classify incoming documents and predict the correct business process, such as AP approval, warehouse receiving, or dispute resolution.

  Business value: Speeds up document routing, reduces manual triage, and supports partner specific processing rules without heavy custom coding.

• 6. Improve quality control for shipping and logistics documents

  Data flow: OpenText Active Documents Trading Grid to Prodigy

  Shipping notices, bills of lading, packing lists, and delivery confirmations exchanged through OpenText Active Documents Trading Grid can be annotated in Prodigy to train models that verify completeness and consistency. These models can flag mismatches between purchase orders, shipment notices, and received goods before they create operational delays.

  Business value: Reduces receiving errors, improves supply chain visibility, and helps logistics teams resolve discrepancies earlier.

• 7. Create a feedback loop for document compliance monitoring

  Data flow: OpenText Active Documents Trading Grid to Prodigy to compliance dashboards

  Documents exchanged through OpenText Active Documents Trading Grid can be sampled for compliance review and labeled in Prodigy based on policy requirements, such as required fields, approved templates, or partner specific mandates. The labeled data can train models that monitor future transactions and flag compliance risks automatically.

  Business value: Strengthens audit readiness, reduces compliance review effort, and provides earlier detection of policy violations.

• 8. Accelerate intelligent document processing pilot programs

  Data flow: OpenText Active Documents Trading Grid to Prodigy to MLOps or ERP systems

  Organizations can use OpenText Active Documents Trading Grid as the source of real business documents and Prodigy as the annotation layer for building proof of concept models. This is especially useful for piloting intelligent document processing in procurement, finance, or logistics before rolling out to ERP, AP automation, or supply chain platforms.

  Business value: Shortens implementation timelines, validates automation use cases with real partner data, and reduces risk before enterprise deployment.