---
sourceDocument: Australia Build workflows
sourceDocumentLink: https://www.servicenow.com/docs/r/australia/build-workflows
Release :
- australia
ft:locale :
- en-US
ft:publication_title :
- Australia Build workflows
ft:clusterId :
- crworkflow
bundleId :
- crworkflow
workflow :
- Creator
---
# Explore
# Exploring Flow generation with images {#ariaid-title1}
Release version: Australia
Updated July 29, 2026
 3 minutes to read
Summarize
 Summarized using AI
This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete.
## Summary of Exploring Flow generation with images
ServiceNow Otto for Creator enables customers to create flows or subflows directly from images by attaching process visuals to Workflow Studio.
The tool generates a flow preview from the image, allowing users to modify and regenerate it, streamlining flow creation based on visual documentation.
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This feature is available through the Flow generation with images skill, which is installed as part of the ServiceNow Otto for Creator (snnowcreator) application, accessible from the ServiceNow Store.
## Key Features
* **Image-based flow creation:** Build multi-step flows or subflows in Workflow Studio by capturing a process in an image and attaching it for automated flow generation.
* **Supported triggers:** Includes scheduled, record (created or updated), Service Level Agreement, inbound email, and Service Catalog triggers, with text directions used to specify trigger types.
* **AI model support:** Compatible with Azure OpenAI, Google Gemini, and Anthropic Claude through ServiceNow's AI Platform, configurable via AI Control Tower and AI Admin Hub.
* **Flow design patterns:** Generated flows use standard design patterns, with triggers and actions configured with appropriate data pill values.
## Best Practices for Writing AI Directions
* **Describe the trigger first:** Clearly specify the flow's trigger and its data conditions before describing actions and logic.
* **Be precise and descriptive:** Use exact and clear descriptions of triggers, record data, actions, and logic, supported by high-quality images if attached.
* **Use correct names:** Refer to actions, flow logic, and tables by their exact names; use hashtags (#) to specify table names and avoid confusion between similarly named tables.
* **Specify flow or subflow upfront:** Begin directions with phrases like "Create a flow that" to clarify the desired output.
* **Number parallel branches:** When describing parallel actions, number each branch to clarify execution order.
* **Use quotation marks for exact values:** Enclose literal data values in quotes to distinguish them from operation names or variables.
* **Review generated flows:** Always verify the generated flow outline and input values to ensure data references and logic align with requirements.
## Practical Benefits for ServiceNow Customers
This capability accelerates flow development by transforming visual process documentation into executable flows, reducing manual configuration effort. It supports improved accuracy in flow triggers and actions through AI-assisted generation and enables easy iterative refinement by reviewing and modifying generated flows. Customers can leverage this to quickly automate processes, improve workflow consistency, and harness AI models integrated within the Now Platform.
Create a flow or a subflow from an image by using ServiceNow Otto for Creator. Capture the detailed process in an image and attach the image to Workflow Studio. ServiceNow Otto for Creator generates a preview of the flow that you can modify and regenerate.
## Activation {#exploring-flow-generation-with-images__section_rzl_d41_qyb}
The skill Flow generation with images is installed with the ServiceNow Otto for Creator (sn_now_creator) application. You can install this application from the [ServiceNow Store](https://store.servicenow.com/sn_appstore_store.do#!/store/home) website.
## Benefits {#exploring-flow-generation-with-images__section_rff_k41_qyb}
Enable flow generation with images to gain these benefits.
* Build a multi-step flow or subflow from an image in Workflow Studio. Supported triggers and actions are configured with appropriate data pill values.
* Use standard flow design patterns.
{#exploring-flow-generation-with-images__ul_ogl_nq1_qyb}
## Supported LLMs {#exploring-flow-generation-with-images__section_wn5_stj_bgc}
You can use Azure OpenAI, Google Gemini, or Anthropic Claude as the AI model provider for Now Assist skills and AI agents. Use the Configuration Controls in [AI Control Tower](https://www.servicenow.com/docs/access?context=ai-model-providers&version=australia&pubname=australia-intelligent-experiences&ft:locale=en-US) to define which options are available, then set the skill-level preferences in the [AI Admin Hub console](https://www.servicenow.com/docs/access?context=manage-large-language-models&version=australia&pubname=australia-intelligent-experiences&ft:locale=en-US). For more information, see [Large language models on the ServiceNow AI Platform®](https://www.servicenow.com/docs/access?context=exploring-large-language-models&version=australia&pubname=australia-intelligent-experiences&ft:locale=en-US).
## Supported trigger types {#exploring-flow-generation-with-images__section_mwk_qvj_tdc}
Flow generation supports a limited number of trigger types. You can use text directions to specify these trigger types.
* Scheduled triggers
* Record triggers
* Created
* Created or Updated
* Updated
{#exploring-flow-generation-with-images__ul_rnt_zvj_tdc}
* Service Level Agreements triggers
* Inbound email triggers
* Service Catalog triggers
{#exploring-flow-generation-with-images__ul_kxw_xvj_tdc}
## General guidelines {#exploring-flow-generation-with-images__section_c4d_wp1_qyb}
Follow these general guidelines when writing AI directions.
Always describe the trigger first
: Describe the flow trigger and its data conditions first. After the trigger, describe the actions and flow logic in the same order that you want them to be in the flow.
Avoid spelling errors
: Avoid misspelling the names of actions, flow logic, or tables. Consider using hash tags to avoid making mistakes with table names.
Be precise and descriptive in your request
: Make sure that your request is precise and descriptive. Describe the flow trigger, record data, actions, and flow logic in as much detail as you can. If you attach an image, make sure to attach a clear, high quality image of the process.
Be succinct and direct in your request
: Start by specifying whether you want to generate a flow or a subflow. For example, use the phrase, "Create a flow that" to generate a flow. Describe each step the flow in order.
Refer to actions, flow logic, and tables by name
: Use action, flow logic, and table names as part of your directions. The closer your directions are to the actual names, the easier it is for the LLM to recognize them. For example, use the text for each or do the following in parallel to refer to those specific flow logic options. For table names, consider using hash tags.
Review the generated flow outline and input values
: Review each action, flow logic, and subflow in the generated flow outline. Review the generated inputs values to confirm that they contain relevant data references.
Use hash tags to refer to data in a specific table
: Use a hash tag to select a specific table name. Hash tags are particularly useful to distinguish between tables that have identical or similar display names such as the User \[sys_user\] and User \[imp_user\] tables.
Use numbers to distinguish the branches of do the following in parallel flow logic
: Add a number to each parallel branch. For example, the directions, "When a P1 incident is created, do the following in parallel: 1. Log its short description and 2. Look up the user assigned to it and send an email," makes it clear that there are two branches.
Use quotation marks to set exact values
: Enclose exact data values in quotations marks to help the LLM distinguish between operation names and data values. For example, the directions, "Log the value, 'incident reopened'" make it clear
that the text "incident reopened" is a data value.