Background & Objectives

This guide will walk you through how to build Agent Studio plugins that return large volumes of data to the AI Assistant.

In this quickstart guide, you will

Build a plugin that fetches 500 accounts from a mock CRM
Set up the plugin to work alongside our Code Interpreter plugin

At the end, your AI Assistant will be able to handle requests like this

Prerequisites

Access to Agent Studio
Access to Structured Data Analysis.
No system APIs needed!

Define your plugin

Navigate to Agent Studio

Go to Agent Studio. In the Plugins tab, select Create

Define your plugin

Define your plugin.

📘 SDA Tip!

It’s important to be descriptive about the data that an SDA plugin returns.

Attribute	Value
Plugin Title	Fetch Accounts
Plugin Description	Returns all Accounts with ID, name, industry, territory, created/modified, last contact & renewal, ARR & MRR, employee count, opportunities (total/open/won/lost), avg deal size, churn rate, NPS, tickets, offices, market share %, growth rate & funding.

Create a trigger

Add a Conversational Trigger

In the Plugin Editor, add a Conversational Trigger and fill it out

Build your process

Connect to the mock CRM

We need an HTTP action that will fetch the large volume of data from the external system.

Create a new HTTP Action

Click ⊕ in the tab bar and create a new HTTP Action

Select Import

Select the Import option (next to the Test button)

Import the API call

Import the following API call

$ curl --location 'https://marketplace.moveworks.com/api/purple-suite/crm/accounts?count=500'

Test

Hit Test

Name your HTTP Action

Name your HTTP Action. It should look something like this.

Save

Save your HTTP action

Attach a Conversational Process

Now let’s connect the HTTP action to your plugin & prepare it for analysis

Add a Conversational Process

In the Plugin Editor, add a Conversational Process & create a new one.

Add an action-based activity

In the Conversational Process Editor add an action-based activity.

Choose your HTTP Action

Choose the HTTP Action you just built.

Configure the Output Mapper

In the activity configuration, under Output Mapper, we will rename the fields to make them more friendly for SDA.

📘 SDA Tip!

It’s important to name fields succinctly & clearly to maximize the performance of SDA against various queries.

1 MAP():
2   items: response.accounts
3   converter:
4     AccountID: item.Id
5     AccountName: item.Name
6     AnnualRecurringRevenue: item.ARR__c
7     AverageDealSize: item.AverageDealSize__c
8     ChurnRate: item.ChurnRate__c
9     ClosedLostOpportunities: item.ClosedLostOpportunities__c
10     ClosedWonOpportunities: item.ClosedWonOpportunities__c
11     DateCreated: item.CreatedDate
12     DateLastModified: item.LastModifiedDate
13     Employees: item.NumberOfEmployees
14     FundingAmount: item.FundingAmount__c
15     GrowthRate: item.GrowthRate__c
16     Industry: item.Industry
17     LastContactDate: item.LastContactDate__c
18     MarketShare: item.MarketSharePct__c
19     MonthlyRecurringRevenue: item.MRR__c
20     NetPromoterScore: item.NPS_Score__c
21     NextRenewalDate: item.NextRenewalDate__c
22     OfficeCount: item.OfficesCount__c
23     OpenOpportunities: item.OpenOpportunities__c
24     SupportTickets: item.SupportTickets__c
25     Territory: item.Territory__c
26     TotalOpportunities: item.TotalOpportunities__c

Launch it

Launch to yourself

Under Audience Settings you can launch it to yourself for testing.

Test it!

Try it out

Try it out! You should see something like the following.

Not seeing the right results?

Verify that SDA is running by checking for the Running analysis progress update

Here are some other questions you could try:

What’s the total ARR of customers in the Tech industry?
Which industry is performing best in Europe?
Which accounts have the most support tickets are are up for renewal soon?

Next Steps

Start building your own plugins for Structured Data Analysis!