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Finance | Project Operations, Human Resources, ...
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Handling User Input for Credit Ratings in D365 F&O Copilot's Sidecar Using X++

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Posted on by 85

Hi everyone,

I'm working on a Copilot for Dynamics 365 Finance and Operations (D365 F&O) using X++. I have successfully implemented the functionality to open the customer list form in D365 Copilot's sidecar. Now, I need to filter and display customers based on their credit ratings (a field available in CustTable).

For example, when I prompt the system with "Provide customer credit ratings," it asks me which credit ratings I want to see. Users might respond with different combinations like:

  • Example 1: "excellent, good or bad and poor"
  • Example 2: "excellent good bad or poor and good"
  • Example 3: "good bad excellent(in next line)

How can I handle these different user input scenarios in X++ to correctly filter and display customers based on their credit ratings?

 

Flow on D365 F&O Copilot's SideCar for Clear Understanding:

  1. Prompting the User:The system, through Copilot in Dynamics 365 Finance and Operations (D365 F&O), prompts the user to provide customer data based on credit ratings.
  2. Prompt on SideCar:Initial Prompt: "Provide me Customer based Credit Ratings."
    Follow-up Question: "Which credit rating do you want to see?"
  3. User Response:
    The user provides the credit ratings in various formats:Example 1: "excellent, good or bad and poor"
    Example 2: "excellent good bad or poor and good"
    Example 3: "good [new line] bad [new line] excellent"
  4. Capturing User Input in Copilot Studio:The user's response is captured as a single string within Copilot Studio.
    This input string is stored in a variable within Copilot Studio.
  5. Sending Data to X++:The captured string (user input) is sent to X++ by saving it in the EventPayload.
    The EventPayload is then utilized through an Event Activity to process the input in X++.
  6. Processing the Input in X++:In X++, the input string needs to be processed to extract individual credit ratings.
    The challenge is to handle the various separators the user might use (e.g., commas, spaces, "and," "or," and line breaks) to correctly parse each credit rating.
    The system must ensure that, like AI models (e.g., Copilot, GPT, or Gemini), it can interpret and parse the input flexibly, regardless of how the user formats the credit ratings.

    Thanks in advance.
I have the same question (0)
  • André Arnaud de Calavon Profile Picture
    301,210 Super User 2025 Season 2 on at
    Hi H.Hassan,

    I think you asked the same question in the Dynamics 365 and Power PLatform preview program group on Viva Engage. Microsoft responded already to your question. They suggested creating an Entity for slot filling. Then AI can find valid credit ratings as input.
     
    Another issue is that the credit rating field is a free text field in Dynamics 365 F&O. You can try creating a Credit rating table in F&O and link this as a lookup to this field and use Dual Write to sync the contents to a Dataverse table. You can query Dataverse tables using natural language.

    Alternatively. in the past, I worked at Staedeon (previously known as To-Increase) where we had a solution with a feature to configure and override lookups for fields in Dynamics 365. 
     
    Once you have a list with valid options from the users' responses, you can apply a filter range using X++ coding in a Copilot extension class.

    Note that I haven't verified myself this scenario. I'm working on another use case to get a list of possible values.
  • H.Hassan Profile Picture
    85 on at
    Hi,
    Thanks for your response.

    Yes, I already posted this question on Viva Engage and received the suggestion to use an Entity for slot filling. However, the reason for posting this again is that I want to handle user-entered prompts in a natural language format, similar to how GPT or Gemini processes input.

    I’m looking for a solution where the system can understand and apply filters based on user input in various formats, like:

    • Example 1: “excellent, good or bad and poor”
    • Example 2: “excellent good bad or poor and good”

    In these examples, the user employs both "or" and "and," and I need the system to correctly interpret and apply filters for all the credit ratings the user enters.


     

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