Enterprise sustainability programs rely heavily on data, especially as ESG reporting continues to evolve under regulatory frameworks across Europe. However, much of this data resides in unstructured formats such as utility bills, fuel invoices, vendor statements, and supplier documents. These documents are often manually processed, leading to time-consuming data entry, spreadsheet consolidation, delayed reporting cycles, inconsistent formats, and increased risk of human error. As a result, audit traceability becomes challenging, validation remains reactive, and mitigation actions are often triggered too late.
A Small Showcase Application
This article presents a small showcase application demonstrating how Pega Intelligent Document Processing can be implemented using GenAI Connect to enable smarter, decision-driven workflows. In this approach, documents are no longer treated as passive attachments but as active data sources that drive core business decisions within a Carbon Mitigation case type.
To see how this is configured in detail,watch the demo : https://youtu.be/4-w-cHvprfo?si=xpDUAjZ_T8EuOJde
From Document Intake to Action
With this approach:
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Users upload invoices or bills directly within the case
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Key ESG parameters are automatically extracted using IDP capabilities via GenAI Connect
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Extracted values are mapped to structured case properties
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Validation rules ensure completeness and accuracy
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Emission calculations trigger instantly
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Threshold breaches automatically initiate mitigation actions
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A subsequent GenAI Connect invocation analyzes the extracted IDP data to assess risk severity and generate mitigation plans aligned to the identified risk levels
This approach combines document understanding (IDP) with decision intelligence (GenAI), transforming unstructured inputs into actionable ESG outcomes within the workflow.
How It’s Implemented
The implementation is driven through Pega GenAI Connect, where document processing and extraction are tightly integrated within the workflow.
Key Configuration Points
- Include Attachments for Analysis
Uploaded invoices and bills are passed as part of the GenAI request payload, enabling the model to directly analyze document content.
- Document-Capable AI Model
A model such as GPT-4o mini is used to support document understanding and structured data extraction.
Prompt Engineering for Structured Output
The prompt is designed to identify and extract key ESG fields from uploaded documents in a structured format.
It focuses on:
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Detecting relevant data points from invoices or bills
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Extracting key fields such as usage values, units, dates, and identifiers
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Ensuring consistent field naming aligned with case properties
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Returning structured, system-consumable output
This ensures that the AI response is accurate, predictable, and directly mappable to Pega properties, enabling seamless integration without additional transformation.
Structured Response Mapping
The generated output is mapped directly to corresponding Pega case properties, enabling:
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Structured data population
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Immediate downstream processing
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Seamless integration with workflow steps
End-to-End Flow
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Documents are analyzed via GenAI Connect
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Key ESG data is extracted in structured format
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Outputs are mapped to case properties
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A subsequent GenAI invocation evaluates risk and generates mitigation actions
This implementation creates a clean, governed, and efficient pipeline, where unstructured documents are directly converted into structured, actionable data within the workflow.
Medium article : https://medium.com/@stellarnexus/integrating-intelligent-document-processing-into-enterprise-workflows-to-transform-documents-into-8fb705325bd7