OpenAI Vision and Fillout Integration

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Automatically process Fillout form submissions: use OpenAI Vision to analyze images uploaded in Fillout, extract key data, and trigger custom workflows. Latenode’s visual editor simplifies setup and scales affordably as your data grows.

Swap Apps

OpenAI Vision

Fillout

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect OpenAI Vision and Fillout

Create a New Scenario to Connect OpenAI Vision and Fillout

In the workspace, click the “Create New Scenario” button.

Add the First Step

Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a OpenAI Vision, triggered by another scenario, or executed manually (for testing purposes). In most cases, OpenAI Vision or Fillout will be your first step. To do this, click "Choose an app," find OpenAI Vision or Fillout, and select the appropriate trigger to start the scenario.

Add the OpenAI Vision Node

Select the OpenAI Vision node from the app selection panel on the right.

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OpenAI Vision

Configure the OpenAI Vision

Click on the OpenAI Vision node to configure it. You can modify the OpenAI Vision URL and choose between DEV and PROD versions. You can also copy it for use in further automations.

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Connect OpenAI Vision

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Run node once

Add the Fillout Node

Next, click the plus (+) icon on the OpenAI Vision node, select Fillout from the list of available apps, and choose the action you need from the list of nodes within Fillout.

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Authenticate Fillout

Now, click the Fillout node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Fillout settings. Authentication allows you to use Fillout through Latenode.

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Configure the OpenAI Vision and Fillout Nodes

Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.

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Run node once

Set Up the OpenAI Vision and Fillout Integration

Use various Latenode nodes to transform data and enhance your integration:

  • Branching: Create multiple branches within the scenario to handle complex logic.
  • Merging: Combine different node branches into one, passing data through it.
  • Plug n Play Nodes: Use nodes that don’t require account credentials.
  • Ask AI: Use the GPT-powered option to add AI capabilities to any node.
  • Wait: Set waiting times, either for intervals or until specific dates.
  • Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
  • Iteration: Process arrays of data when needed.
  • Code: Write custom code or ask our AI assistant to do it for you.
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Save and Activate the Scenario

After configuring OpenAI Vision, Fillout, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.

Test the Scenario

Run the scenario by clicking “Run once” and triggering an event to check if the OpenAI Vision and Fillout integration works as expected. Depending on your setup, data should flow between OpenAI Vision and Fillout (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.

Most powerful ways to connect OpenAI Vision and Fillout

Fillout + Airtable + Slack: When a new submission is received in Fillout, create a record in Airtable, and send a notification to a Slack channel.

Fillout + Slack: When a new form submission is received in Fillout, send a notification to a Slack channel.

OpenAI Vision and Fillout integration alternatives

About OpenAI Vision

Use OpenAI Vision in Latenode to automate image analysis tasks. Detect objects, read text, or classify images directly within your workflows. Integrate visual data with databases or trigger alerts based on image content. Latenode's visual editor and flexible integrations make it easy to add AI vision to any process. Scale automations without per-step pricing.

About Fillout

Use Fillout forms in Latenode to collect data and instantly trigger workflows. Instead of manual exports, automate follow-ups, database updates, or personalized emails based on form responses. Latenode lets you parse, transform, and route Fillout data to any app with full control and no per-step pricing.

See how Latenode works

FAQ OpenAI Vision and Fillout

How can I connect my OpenAI Vision account to Fillout using Latenode?

To connect your OpenAI Vision account to Fillout on Latenode, follow these steps:

  • Sign in to your Latenode account.
  • Navigate to the integrations section.
  • Select OpenAI Vision and click on "Connect".
  • Authenticate your OpenAI Vision and Fillout accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I automatically analyze submitted receipts using AI?

Yes, you can! Latenode lets you automate receipt analysis from Fillout forms using OpenAI Vision, triggering actions based on the extracted data. Enjoy seamless data processing.

What types of tasks can I perform by integrating OpenAI Vision with Fillout?

Integrating OpenAI Vision with Fillout allows you to perform various tasks, including:

  • Automatically categorize images submitted through Fillout forms.
  • Extract text from documents uploaded via Fillout using OCR.
  • Moderate content by identifying inappropriate images.
  • Analyze sentiment of visual responses collected in Fillout.
  • Update Fillout records with insights extracted from images.

How does Latenode handle OpenAI Vision API key security?

Latenode securely stores your OpenAI Vision API keys using encryption and provides role-based access control for enhanced security.

Are there any limitations to the OpenAI Vision and Fillout integration on Latenode?

While the integration is powerful, there are certain limitations to be aware of:

  • OpenAI Vision has rate limits on image analysis requests.
  • Large file sizes can impact processing time.
  • Custom model training requires a separate OpenAI subscription.

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