Whenever I speak with SAP customers and partners, one question repeatedly surfaces: "Amit, how do we handle these massive SAP EarlyWatch and Oracle AWR reports without spending endless hours sniffing through them with AI tooling?" After I published my First Copilot Studio article last year. Frankly, after hearing this question countless times, I decided it was finally time to put pen to paper—or rather, fingers to keyboard—and unravel this mystery once and for all, with all options on table. And, trust me, there's enough caffeine behind this article to power a small data center! SAP admins and ABAP Developers are all too familiar with the daunting task of analyzing extensive SAP EWA and Oracle AWR reports, typically surpassing a hundred pages each. Fortunately, AI offers practical ways to automate this tedious task with solid summarization tooling. The good news? You don't have to settle for just one option—there are SIX practical, AI-driven approaches available (last option might be debatable!), specifically designed around your team's technical abilities and your organization's current AI adoption maturity. After fielding numerous inquiries from customers and partners looking to optimize their handling of these complex reports, I realized it was essential to clarify these pathways. So, whether your enterprise is just starting its AI journey or already well-versed in sophisticated deployments, there's a tailored solution ready for you to adopt. By aligning these approaches with your enterprise's skillset and readiness for AI adoption, you can seamlessly streamline your report summarization processes. Let's explore each option to find the best fit for your Tech. team.
Comparative Analysis of AI-Driven Methodologies on Microsoft Cloud platform -
Approach | Principal Features | Required Expertise | Implementation Complexity | Technical Advantages | |
1 | Microsoft Power Platform with AI Builder | Automated PDF extraction, GPT summarization | Low-code | Low | Rapid setup, minimal coding |
2 | Microsoft Copilot Agent builder Integrated with SharePoint | Generative AI for document summarization, interactive queries | Low-code | Low-Medium | Interactive, secure internal access |
3 | Microsoft Copilot Studio builder Integrated with SharePoint | Generative AI for document summarization, interactive queries | Low-code | Low-high | Interactive, secure internal access |
4 | Azure AI Agent Leveraging Azure AI Foundry and RAG | Semantic search, RAG integration, vector databases | Pro-code | Medium-High | Enhanced accuracy, scalable |
5 | Advanced Custom AI/ML Model Development | Customized NLP models, Azure Document Intelligence | Pro-code | High | Highly tailored analytical insights |
6 | OmniParser Vision-based GUI Automation | GUI-based visual parsing, OmniParser V2 for LLM-driven automation | Pro-code | Medium-High | Flexible direct GUI interaction |
Technical Implementation Steps -
1. Microsoft Power Platform with AI Builder (Low-code)
- Prerequisites: Microsoft Power Platform subscription, AI Builder license.
- Implementation Steps:
- Store reports in SharePoint or OneDrive.
- Execute text extraction via AI Builder Text Recognition.
- Configure AI Builder summarization using Power Automate flows.
- Automate summary distribution via Microsoft Teams or email.
- Documentation: Microsoft Power Automate AI Builder
Sample of Power Platform extractor tool


2. Microsoft Copilot Agent with SharePoint Integration and code-Interpreter (Low-code)
- Prerequisites: Microsoft 365 subscription with Copilot enabled, existing SharePoint libraries.
- Implementation Steps:
- Upload and index SAP EWA and Oracle AWR documents into SharePoint.
- Enable Copilot integration to allow natural-language queries.
- Provide access via Microsoft Teams or SharePoint interface.
- Documentation: Microsoft Copilot with SharePoint
- Ref my previous article with details to setup –
Ready to Transform SAP Management? Microsoft Copilot Agents Are Here!
3. Microsoft Copilot Studio with SharePoint (Low-code)
- Prerequisites: Microsoft 365 subscription with Copilot enabled, existing SharePoint libraries.
- Implementation Steps:
- Upload and index SAP EWA and Oracle AWR documents into SharePoint.
- Enable Copilot integration to allow natural-language queries.
- Provide access via Microsoft Teams or SharePoint interface.
- Storing selected bytes from SAP EWA report in SharePoint sheet for review
- Trigger email with SharePoint summary report
- Documentation: Microsoft Copilot with SharePoint
- Refer my previous article with details for this setup -
Unleashing the Power of Microsoft Copilot Studio for SAP Technical Reports
4. Azure AI Agent with Azure AI Foundry and Azure AI Search / RAG enabled (Pro-code)
- Prerequisites: Azure subscription, Azure Cognitive Search, Azure OpenAI (GPT-4), Azure AI Foundry.
- Implementation Steps:
- Configure Azure AI Search to index reports into semantic vector stores.
- Implement Retrieval-Augmented Generation (RAG) pipeline using Azure AI Foundry and GPT-4.
- Setting up Azure AI Agent services integrated with pipeline and model selected
- Deploy a specialized SAP EWA Agent for automated parsing and insights.
- Dispatch all information on Technical mailbox for review in automated way
- GitHub Example: Azure Search & OpenAI Implementation
5. Custom AI/ML Model with Azure AI Document Intelligence (Pro-code)
- Prerequisites: Azure subscription, Azure AI Document Intelligence, Azure AI Foundry, expertise in NLP and ML model fine-tuning.
- Implementation Steps:
- Train and fine-tune NLP models specifically on historical SAP EWA and Oracle AWR data.
- Use Azure Document Intelligence to extract structured and semi-structured data.
- Implement advanced analytics, including anomaly detection and trend analysis.
- Deploy custom models via Azure AI Foundry.
- Documentation: Azure AI Foundry
6. Microsoft OmniParser V2: Vision-based GUI Automation (Pro-code) for scanning PDF live and extract the required data for analysis.
- Prerequisites: Development environment setup, OmniParser SDK, vision model training capability, LLM APIs access.
- Implementation Steps:
- Set up OmniParser SDK for vision-based parsing on your system.
- Train vision models for accurate GUI recognition for PDF content.
- Integrate OmniParser V2 with Large Language Models (LLMs) for intelligent automation.
- Implement automation scripts for GUI interactions without backend integration.
- GitHub Reference: OmniParser Repository
Real-world Benefits for SAP Basis and technical Teams
Automating these report summaries provides:
- Major time savings for SAP Basis and Oracle DBA teams.
- Rapid identification and proactive management of critical issues.
- Easier collaboration through simplified and actionable insights.
- Coordinate with the global SAP team to receive summarized results via email.
- Proactive monitoring improves SLA over time and reduces the risk of missing critical SAP system updates.
Select the method aligned with your team's skillset:
- Low-Code Teams: Power Platform or Copilot Studio.
- Pro-Code Teams: Azure AI Agents with Foundry, advanced ML models, or OmniParser v2.
Disclaimer: I frequently receive requests from customers and partners seeking effective ways to automate and streamline complex report analysis. These repeated conversations inspired me to document these AI-driven strategies. This article was crafted with assistance from a Writing Coach AI agent powered by GPT-4.5.
AI isn’t the future—it’s now. Keep building, keep learning!
-Amit Lal
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