How to Create Custom Inspection Reports Natively in a Canvas App?
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After you leave this case study, you will NOT be able to return to it. To start the case study To display the first question in this case study, select the “Next” button. To the left of the question, a menu provides links to information such as business requirements, the existing environment, and problem statements. Please read through all this information before answering any questions. When you are ready to answer a question, select the “Question” button to return to the question. Background Fabrikam Inc. is an energy provider that operates wind and solar farms across multiple countries and regions. The company uses Microsoft Power Platform to manage asset maintenance, technician workflows, and predictive analytics. Field technicians use canvas apps on mobile devices to capture inspection and repair data. Operations managers use model-driven apps to monitor asset performance and maintenance history. The company plans to enhance its platform by introducing AI-driven insights, improving reuse across applications, and establishing a formal application lifecycle management (ALM) strategy. Current environment Applications Field technicians use an outdated mobile app to log maintenance activities and capture asset readings in SharePoint Online. Operations managers use a model-driven app to review maintenance records and asset performance trends. Development practices Developers build and modify applications directly in the production environment. There is NO structured ALM process. Solutions are NOT consistently used to package or deploy application components. Reusable components are inconsistently implemented across apps, leading to duplication. AI integration Fabrikam Inc. plans to actively explore generative AI usage as part of the next phase of work. Business requirement Application development The outdated mobile app must be replaced with a new app that supports responsive design principles, provides full control over the UI, and allows technicians to take and upload photos directly from their mobile devices. The new app for the field technicians requires the name of the technician to be persisted on the home screen only. In addition, work orders must be displayed within a gallery. All new apps must connect to a scalable, cloud-based relational data store. Apps must support efficient data entry for technicians in the field. Reusable UI elements must be implemented to reduce duplication. AI capabilities The company requires a generative AI solution to manage customer complaint responses and create custom inspection reports that align to an existing template. Customer complaint responses must be generated in applications and based on emails being sent to a mailbox. Custom AI development must be minimized. Generative AI reusability Generative AI solutions must accept dynamic inputs to adapt to different scenarios. Generative AI solutions must be reusable across different Power Platform services. Extensibility Custom UI form components must be reusable across applications. Use of server-side custom code must be minimized where possible. Technical requirements Application lifecycle management (ALM) Separate environments must be used for development, testing, and production. Solutions must be used to package application components, segmented based on functional areas. Managed solutions must be deployed to the production environment. Validation must occur before deployment to production. Data processing Aggregated values across related rows must be displayed for reporting. Calculations must update automatically as new data is entered. Calculation data must be limited to a maximum length of 10. Issues Duplicate logic exists across multiple canvas apps. Developers frequently overwrite changes in production. Generative AI solutions produce inconsistent outputs due to missing or inconsistent inputs. Maintenance metrics are not consistently calculated across related rows. You need to provide a solution for field technicians to create custom inspection reports natively within the new app. What should you do?
Community Insight
It tests whether you can map a generative-AI report-generation requirement to a reusable AI Builder prompt with dynamic inputs, rather than to document-template or reporting features.
Fabrikam needs field technicians to generate custom inspection reports inside the new canvas app while minimizing custom AI code. This page explains why an AI Builder custom prompt is the correct native, reusable generative AI approach (C), not a Word template or paginated report.
Choosing a Word template because the reports must align to an existing template; that produces static documents through Power Automate and does not satisfy the native generative AI requirement.
Community Discussion (3 comments)
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Expert Analysis
Why the Answer Is Correct
A custom prompt in AI Builder is the native Power Platform generative AI feature that accepts dynamic inputs and can be invoked directly from the canvas app, satisfying the requirement to create inspection reports inside the new app. The prompt can be authored with instructions that shape the output to Fabrikam's existing inspection-report template while keeping custom AI development and server-side code to a minimum. Because prompts are reusable across Power Platform services, they also support the stated reusability requirement better than an app-specific document template. The field technician supplies the dynamic work-order and inspection data, and the prompt returns structured report content for the app.
Why the Other Options Are Wrong
A Word template generates a document by merging data into predefined placeholders, typically through Power Automate or an Office integration, and is not a generative AI solution that can be called natively inside the app. A paginated report is a reporting and pagination feature for large datasets, not an in-app generative report-authoring tool for technicians. Both alternatives miss the case study's explicit generative AI and reusable-prompt requirements, even though the phrase "align to an existing template" can make Word templates look tempting.
Community Comment Notes
One learner quoted the case requirement that reports "align to an existing template" and selected a Word template, treating template alignment as the deciding clue. Another learner, aed747e, argued that an AI Builder custom prompt satisfies the generative AI requirement through natural-language instructions and dynamic inputs inside the canvas app. A third comment also favored Word templates, but that reasoning conflates document template merging with the reusable generative AI prompt demanded by the scenario.
Official Reference
Exam Strategy
In this case study, tie the answer to the AI capabilities and reusability requirements rather than the word "template" alone. A custom prompt is the low-code generative AI option that can be called natively from the canvas app and reused across Power Platform services.
Frequently Asked Questions
Why not use a Word template for the inspection reports?
A Word template produces a document from data, usually through Power Automate, and is not a generative AI prompt inside the app. The case requires reusable generative AI with dynamic inputs and minimal custom code.
Can an AI Builder custom prompt be reused across Power Platform services?
Yes. Prompts can be invoked from Power Apps, Power Automate, and Copilot Studio, matching Fabrikam's requirement for reusable generative AI solutions.