The AI Assist: Custom Prompt action in SmartSuite lets you integrate large language models (LLMs) like OpenAI’s GPT directly into your automated workflows. This action gives you full control over how data from your SmartSuite records is passed to AI models and how the results are structured for use in downstream automation steps.
Overview
The AI Assist: Custom Prompt action allows you to:
Compose a tailored prompt using dynamic field data
Choose the AI provider and model
Define expected outputs in a structured format
Use AI-generated results in subsequent automation steps
Adding the AI Assist Action
1. Choose a Trigger
Set up a trigger that determines when the automation runs and which record is used as the data source. Example:
Trigger: When a Record is Created
Action: Evaluate the new record with AI and extract data from it to use in subsequent automation actions.
2. Select the AI Assist: Custom Prompt Action
Under Integrations, choose AI Assist.
Select Custom Prompt to start configuring your AI action.
Setting Up a Connection to an AI Provider
Before using AI Assist, you must connect your SmartSuite workspace to an LLM provider such as OpenAI.
Steps:
Select a Provider (e.g., OpenAI)
Enter your API key
Name your connection
Each Solution Manager can create their own connections. Multiple connections to the same provider are supported within a solution.
After setup, the connection becomes available to all Solution Managers in that solution. See them displayed in the Existing Connections section (screenshot below).
You may later remove connections, with a warning if automations will be affected.
For more information about connecting your AI Platform, please see this help article: AI Assist: Connecting Your Provider
Selecting a Model
Once connected, you’ll choose a model for each Custom Prompt action. Each provider displays a list of available models, such as:
gpt-4o,gpt-4o-minigpt-3.5-turbo
Each model includes:
A short description
Icons indicating whether the model supports:
Images
PDF Files
A cost indicator (
$to$$$$)
Note: You can only use one model per Custom Prompt action.
Composing the Prompt
Use a mix of static text and dynamic variables (from triggers or previous automation steps) to build your prompt.
You can reference:
Fields from single-record outputs (e.g., “Trigger: Product Description”)
Fields from multi-record outputs (e.g., “Find Orders: Order Total”)
Attachments and multi-value fields
Adding Fields as Reference Data
To add a field from the trigger or a previous action:
Click on the blue "plus" icon in the right hand corner of the Prompt input.
Select a field from the displayed selection list, OR
Click the back arrow (<) in the top left corner to select another source
Once clicked, you can select the trigger or a prior action as the data source
After you make your selection, you can choose from a list of available data fields to insert into your prompt.
Prompt values are sent to the AI, including both the text and referenced data values.
Adding Attachments to the Prompt
To add a file to your prompt contents:
Click on the blue "+" icon in the Attachments input
Select the source for the attachment. You can source files from three different locations:
Fields from the Trigger
Fields from another Action
Manually uploaded files
Prompt Examples:
“Translate
Trigger: Product Descriptionto Italian”“Calculate the average of
Action: Order Amountfor the current month”
Or more complex:
Respond as a corporate compliance expert. Evaluate this policy and recommend updates based on industry best practices.
Policy: Policy Name
Purpose: Policy Purpose
Scope: Policy Scope
Statement: Policy Statement
Defining the Output
The output defines the format you expect the AI to return. You can choose from:
1. Simple Output
Returns raw text
Best for free-form responses
Treated as a multi-line Text Area in SmartSuite
2. Custom Output
Custom outputs can create more complex, structured data that can be used later in your automation workflow.
To create Custom output:
Click on the Custom tab under the Output section.
Define the structured data to return by clicking Add Output to build the data structure.
Output values can contain their own instructions that help "teach" the AI model how to format the specific value.
Configuring these Custom output values allows downstream automations to use the response in fields and logic conditions.
Custom Output Types:
Single Value (e.g., Title, Price)
List of Values (e.g., List of Emails)
JSON Object or Array
Each output field includes:
Name (required)
Type (Text, Number, Boolean, etc.)
Optional instruction to guide the AI
When using Custom Output, SmartSuite appends a system prompt to enforce JSON formatting.
Supported Field Types for Output
Custom Outputs can return any of the following:
Text
Number
Yes/No (Boolean)
Date / Time / Date & Time
Email
URL
Phone
Single Select
Duration
SmartSuite maps these data types automatically to ensure compatibility with downstream actions.
Defining a Custom Output
When configuring a Custom Prompt, you can define a Custom Output to structure the AI’s response in a predictable format. This makes it possible to use the returned values directly in later automation steps (e.g., updating a record or sending an email).
Custom Outputs consist of one or more output fields, each with a clearly defined type, name, and optional instructions to guide the LLM’s response formatting.
⚠️ When defining a Single Select output, you must ensure the response exactly matches one of the options configured in the target SmartSuite field. For example, if the field accepts “Open”, “In Progress”, and “Closed”, the LLM must return one of those values without variation.
Custom Output Structure Options
You can return:
A Single Value (e.g., translated text, calculated score)
A List of Values (e.g., list of customer names)
A JSON Object (multiple structured fields)
A List of JSON Objects (e.g., grouped or tabulated outputs)
Each field in your Custom Output must include the following:
Property | Description |
Name | The unique label for the output field |
Type | One of the supported SmartSuite field types |
Instruction (optional) | Additional guidance for the AI to produce the correct format |
Example: JSON Object Output
{ "Response Format": { "Type": "Object", "Name": "Response", "Properties": [ { "Name": "Priority", "Type": "Single Select", "Instruction": "Set to one of the following: High, Medium, Low" }, { "Name": "Due Date", "Type": "Date", "Instruction": "Return in YYYY-MM-DD format" } ] } }Tips for Formatting Output Correctly
Dates & Times: Use ISO 8601 format to ensure SmartSuite parses them correctly.
Single Select Fields: Match values exactly, including case and spelling.
Phone Numbers: Consider using a normalized format like
+1 (123) 456-7890.Lists of Values: Return each item as an array entry, not a comma-separated string (unless instructed).
Example: List Output
{ "Response Format": { "Type": "List", "Name": "Top Customers", "List Item": "String", "Instruction": "Return the top 5 customer names as an array" } }Adding Output Instructions
While not required, adding clear Instructions improves accuracy and helps guide the AI model in generating valid data types.
Examples:
"Return in YYYY-MM-DD format.""Choose from one of the following: Yes, No.""Generate a list of values using the +1 (XXX) XXX-XXXX phone format."
These instructions are not included in the output but are used to shape the AI’s response.
Validating and Using Custom Outputs
Once defined, Custom Outputs are:
Validated during configuration and test runs
Available in later automation steps via variable pills
Mapped into SmartSuite fields, provided the formats align
If a Custom Output is not compatible with the selected SmartSuite field, automation will show a configuration error.
Including precise output definitions ensures reliable AI behavior and smooth integration into SmartSuite workflows. Always test with realistic data before enabling your automation live.
Using the Output in Automations
Once the Custom Prompt returns data, you can use that output in any of the following actions:
Create / Update / Delete Record
Send Email
Find Records
Conditional Branching
Looping
Each returned value becomes available for field mapping or decision-making logic.
Working with Attachments
If the source data includes a file (such as a PDF resume), SmartSuite will attempt to send that file to the LLM—provided the model supports file input. Ensure your prompt explicitly references the file.
Example Use Cases
Trigger | Prompt | Output Format |
New resume submitted | Summarize resume with candidate name, experience, and skills | JSON object with structured fields |
Order approved | Convert “Order Total USD” to local currency | JSON number |
Quote dataset retrieved | Group quotes by contact | List of objects with contact names and quote IDs |
Email received | Categorize email topic | Single select string output (e.g., Sales, Support) |
Best Practices
Use Custom Outputs when results are needed for additional automation steps.
Include clear instructions in the prompt to improve accuracy.
Test your prompt and model selection before enabling the automation.
For sensitive data, ensure you are using secure API keys and understand the provider’s data policies.
Troubleshooting
Prompt is invalid: Make sure all required fields are added and that the prompt is not empty.
Output not usable: Check that the Custom Output format aligns with the fields you want to use.
LLM model limitations: Some models may not support attachments or large data sets.
FAQs
Can I use multiple LLMs in one automation?
No. Each Custom Prompt action can use only one model at a time.
Can I switch models later?
Yes, but SmartSuite will validate compatibility with your prompt and output settings.
Can I use multiple Custom Prompts in a single automation?
Yes. Each step can have its own prompt, model, and output structure.