Automating Customer Agreement Analysis Using Power Automate

Hi Aviral Agrawal

For you to receive the best suggestion and guidance about your concern with Power Automate, I recommend posting your scenario in the Microsoft Power Platform Community Forum Thread. This forum is dedicated to Power Automate and is actively monitored by experienced users, Microsoft partners, and engineers who can provide detailed guidance and share best practices.    

Apologies for redirecting you to a different community as I'm a forum moderator, my primary role is to guide users toward the appropriate resources and support channels and the category you initially posted in primarily focuses on Microsoft 365-related topics, therefore I may not have the depth of expertise needed for your questions.    

However, I did find this article can provide some insights: How Big Law Firms Can Use Power Automate for Document Automation

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For more details, please reach out to Power Automate forum.

I hope everything gets sorted out soon.

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Yes, this is feasible in principle with Microsoft 365 and Power Platform, but it requires combining several capabilities and designing the process carefully. Out of the box, Microsoft tools can reliably automate extraction, classification, routing, and human review of contracts; fully automated “legal judgment” (e.g., deciding compliance) still needs legal oversight.

A practical architecture for the scenario can be built with these components:

1. Document intake and storage
   • Store incoming customer agreements (Word/PDF) in a SharePoint document library.
   • Apply a document processing model (unstructured contract model) to that library to:
     • Identify which files are contracts.
     • Extract key fields (parties, dates, fees, termination, governing law, etc.).
   • This pattern is used in the Microsoft 365 contract management solution, where documents are uploaded to SharePoint, a model classifies them as “contract,” and key data is extracted for stakeholders.
2. AI-based contract understanding
   • Use document processing / AI Builder models for contract processing to automatically extract structured information from the agreement.
   • For Microsoft 365-based solutions, this is described as:
     • “Create models to identify and classify your contract files and then extract the appropriate data from them.”
   • In Power Automate, a prebuilt contract processing model can be called in a flow to extract information from a contract and pass the result into a Data operation (Compose) for further logic and downstream processing.
3. Workflow orchestration with Power Automate
   • Trigger: “When a file is created or modified” in the SharePoint library.
   • Steps (aligned with the contract management reference solution):
     1. Call the contract/document processing model to classify and extract data.
     2. Update metadata (e.g., set Status = "In review").
     3. Post an adaptive card to a dedicated Teams channel (e.g., “Contract Management”) summarizing extracted key fields and asking for approval/review.
     4. Use a condition in the flow to branch on the review outcome (approved/rejected/needs changes).
     5. For approved contracts, send details to downstream systems (e.g., payment or ERP) or a “ready for signature” list.
     6. For rejected or risky contracts, notify the legal/management team for deeper review.
4. Human-in-the-loop review and collaboration
   • Use Microsoft Teams with a channel connected to the SharePoint library so stakeholders can see all contracts and their status.
   • The reference solution shows:
     • Contracts visible in Teams for approval or rejection.
     • Power Automate flows that move contracts through the approval process and notify stakeholders via Teams posts.
   • This pattern can be extended so legal reviewers see AI-extracted clauses and then mark:
     • Non-compliant clauses.
     • Unfavorable or risky terms.
     • Clauses not applicable to a product supplier like Jabra Connect India Pvt Ltd.
5. Summaries, risk flags, and management views
   • AI models provide structured outputs (e.g., parties, dates, amounts, key terms) that can be used to:
     • Populate a SharePoint list of contracts with business-friendly columns (Client, Contractor, Fee amount, Status, Risk level, etc.).
     • Build Power BI dashboards to analyze contract portfolio, risk categories, and trends.
   • A similar pattern is used in the “manage contracts” and “handle incoming documents” scenarios, where extracted metadata is stored in SharePoint and then surfaced via lists, Teams, and Power BI.
6. Automated emails and summaries
   • Power Automate can generate and send:
     • A summary email to management with key extracted fields and review status.
     • A draft email template highlighting concerns, populated with AI-extracted data and reviewer inputs.
   • For example, after review:
     • If Status = “Risk identified,” the flow can assemble a short summary of flagged clauses and send it to management or legal.
7. Extending toward clause-level risk logic
   • Out of the box, document processing models focus on extraction and classification, not full legal risk assessment.
   • However, once key fields and clause texts are extracted, Power Automate can apply business rules (conditions) such as:
     • If governing law ≠ preferred jurisdiction → flag as “Non-standard jurisdiction.”
     • If liability cap is missing or above threshold → flag as “Liability risk.”
   • These rules can drive:
     • Risk labels in SharePoint.
     • Conditional routing (e.g., always send high-risk contracts to senior legal review).
8. Reliability, security, and operations
   • Reliability: Use retry policies and monitoring/alerts (for example, Application Insights for cloud flows) to handle transient failures in document processing and SharePoint/Dataverse connections.
   • Security:
     • Use role-based access control so only authorized users can see extracted contract data.
     • Data in transit and at rest is encrypted in Power Automate and Dataverse.
     • Follow the principle of least privilege for service accounts and app users.
   • Operational excellence: Store solution assets in source control and use Dataverse solutions and ALM practices to promote from development to test to production.
9. Feasibility vs. expectations
   • Feasible today with Microsoft tools:
     • Uploading agreements (Word/PDF) and automatically classifying them as contracts.
     • Extracting key data and clauses using document/contract processing models.
     • Routing for review via Power Automate and Teams, with adaptive cards and approvals.
     • Generating structured summaries and emails based on extracted data and rule-based risk flags.
   • Still requires legal oversight:
     • Final judgment on “non-compliant,” “unfavorable,” or “not applicable” clauses should be made by legal professionals, with AI used to surface and pre-structure the content, not to replace legal review.

In summary, Power Automate combined with Microsoft 365 document processing, SharePoint, Teams, and AI models can automate a large portion of the intake, extraction, routing, and summarization of customer agreements. It can generate draft summaries and emails and highlight potential issues based on configured rules, while legal and management retain final decision-making.

References:

• Streamline document processing with AI Builder
• Scenario: Handle incoming documents with document processing for Microsoft 365
• Manage contracts using a Microsoft 365 solution
• Step 3. Use Power Automate to create the flow to process your contracts
• Use the contract processing prebuilt model in Power Automate (preview)
• Extract and map information from unstructured content
• SLB enhances productivity with Power Platform and AI