An analyzer in Azure Content Understanding within Foundry Tools can be used for this scenario.
Prebuilt Invoice Support: It offers prebuilt invoice analyzer templates specifically trained to identify common transactional data out of the box.
Schema-Driven Extraction: Instead of manual prompt engineering or tedious labeling, you can supply a strict JSON schema containing the specific fields you need.
Nested Values & Layouts: It handles hierarchical, nested elements (such as itemized tables, nested line items, or customer details) and maps them cleanly into arrays or structured objects.
Web App Integration: Activating the analyzer creates a highly scalable REST API endpoint. Your invoice-processing web app can query this endpoint to receive clean, machine-readable structured JSON payloads ready for downstream expense calculation.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/overview

B: Generative AI tools can assist customer service agents by automatically drafting responses to customer inquiries, providing personalized and context-aware solutions. This helps agents improve efficiency, reduce workload, and enhance customer satisfaction.
D: DALL E3, developed by OpenAI, is a cutting-edge generative AI model designed to create images from text descriptions.
Reference:
https://medium.com/@eastgate/top-7-generative-ai-models-tools-for-text-image-and-video-creation-237a0de231b1

Deployment options
Azure AI Foundry provides several deployment options depending on the type of models and resources you need to provision. The following deployment options are available:
* Standard deployment in Azure AI Foundry resources
* Deployment to serverless API endpoints
* Deployment to managed computes
Serverless API endpoint
This deployment option is available only in Azure AI hub resources. It allows you to create dedicated endpoints to host the model, accessible through an API. Azure AI Foundry Models support serverless API endpoints with pay-as-you-go billing, and you can create only regional deployments for serverless API endpoints.
Reference:
https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/deployments-overview

Azure OpenAI Service can generate text based on user prompts. It leverages GPT (Generative Pre-trained Transformer) models that are trained to understand and generate human-like text.
Users interact with these models by providing a prompt, and the model attempts to produce the most likely continuation or completion of that text.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models