AB-410: Building Intelligent ApplicationsDemo

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 improve its platform by introducing AI-driven insights, increasing reuse across applications, and putting a formal application lifecycle management (ALM) strategy in place.

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• Field technicians use an outdated mobile app to log maintenance activities and capture asset readings in SharePoint Online.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, causing 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• The outdated mobile app must be replaced with a new app that supports responsive design principles, provides full control over the UI, and lets technicians take and upload photos directly from their mobile devices.
• The new app for the field technicians requires the technician name to be persisted on the home screen only. In addition, work orders must be shown 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.