OpenAI Vision and Recruitee Integration

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Automatically screen resumes in Recruitee using OpenAI Vision to extract skills and experience, then use Latenode's visual editor to set up automated shortlisting logic. Scale affordably by paying only for execution time.

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OpenAI Vision

Recruitee

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect OpenAI Vision and Recruitee

Create a New Scenario to Connect OpenAI Vision and Recruitee

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 Recruitee will be your first step. To do this, click "Choose an app," find OpenAI Vision or Recruitee, 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 Recruitee Node

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

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Authenticate Recruitee

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

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Configure the OpenAI Vision and Recruitee 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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Set Up the OpenAI Vision and Recruitee 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, Recruitee, 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 Recruitee integration works as expected. Depending on your setup, data should flow between OpenAI Vision and Recruitee (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 Recruitee

Recruitee + Slack: When a new candidate is added to Recruitee, a notification is sent to a Slack channel to inform the HR team.

Recruitee + Google Sheets: When a new candidate is added to Recruitee, their information is added to a Google Sheet for tracking and analysis.

OpenAI Vision and Recruitee 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 Recruitee

Automate your hiring process with Recruitee in Latenode. Trigger workflows on new applications to screen candidates, send automated messages, and update other systems. Connect Recruitee to HR tools for seamless data flow and custom talent pipelines. Simplify recruiting tasks using Latenode's visual editor and scaling options.

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FAQ OpenAI Vision and Recruitee

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

To connect your OpenAI Vision account to Recruitee 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 Recruitee accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I automatically screen resumes with images?

Yes, using Latenode, analyze profile pictures with OpenAI Vision to assess professionalism, then update Recruitee applications automatically. Streamline initial screening effortlessly.

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

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

  • Analyze candidate photos for brand alignment automatically.
  • Extract skills from images of candidate portfolios and resumes.
  • Flag inappropriate content in submitted visual materials.
  • Categorize candidates based on perceived role suitability.
  • Automate initial resume screening based on visual data.

Does Latenode support custom OpenAI Vision models?

Yes, Latenode supports custom models and advanced configurations for OpenAI Vision. Integrate them seamlessly into your Recruitee workflows using our low-code platform.

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

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

  • Rate limits of both OpenAI Vision and Recruitee APIs apply.
  • Complex visual analysis may consume more OpenAI Vision credits.
  • Accuracy of visual analysis depends on image quality.

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