How to connect OpenAI Responses and Bland AI
Create a New Scenario to Connect OpenAI Responses and Bland AI
In the workspace, click the βCreate New Scenarioβ button.

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

Add the OpenAI Responses Node
Select the OpenAI Responses node from the app selection panel on the right.

OpenAI Responses
Configure the OpenAI Responses
Click on the OpenAI Responses node to configure it. You can modify the OpenAI Responses URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the Bland AI Node
Next, click the plus (+) icon on the OpenAI Responses node, select Bland AI from the list of available apps, and choose the action you need from the list of nodes within Bland AI.

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Authenticate Bland AI
Now, click the Bland AI node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Bland AI settings. Authentication allows you to use Bland AI through Latenode.
Configure the OpenAI Responses and Bland AI Nodes
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Set Up the OpenAI Responses and Bland AI 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 donβt 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 Responses, Bland AI, and any additional nodes, donβt 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 βRun onceβ and triggering an event to check if the OpenAI Responses and Bland AI integration works as expected. Depending on your setup, data should flow between OpenAI Responses and Bland AI (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect OpenAI Responses and Bland AI
OpenAI Responses + Bland AI + Slack: When a new response is received from OpenAI, it's analyzed for sentiment by Bland AI. The original response and the sentiment analysis results are then posted to a specified Slack channel.
Bland AI + OpenAI Responses + Google Sheets: Analyze customer feedback calls using Bland AI to extract key insights. Then use OpenAI to generate summaries of those insights and save both the insights and the summaries to a Google Sheet for tracking and analysis.
OpenAI Responses and Bland AI integration alternatives
About OpenAI Responses
Need AI-powered text generation? Use OpenAI Responses in Latenode to automate content creation, sentiment analysis, and data enrichment directly within your workflows. Streamline tasks like generating product descriptions or classifying customer feedback. Latenode lets you chain AI tasks with other services, adding logic and routing based on results β all without code.
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About Bland AI
Use Bland AI in Latenode to automate content creation or rewrite existing text. Streamline your marketing or support workflows by generating tailored responses. Integrate it directly into your Latenode scenarios and use visual tools to manage prompts, route results, and scale AI tasks without complex coding.
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See how Latenode works
FAQ OpenAI Responses and Bland AI
How can I connect my OpenAI Responses account to Bland AI using Latenode?
To connect your OpenAI Responses account to Bland AI on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select OpenAI Responses and click on "Connect".
- Authenticate your OpenAI Responses and Bland AI accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automatically moderate OpenAI content using Bland AI?
Yes, you can! Latenode enables seamless workflows, letting you flag inappropriate OpenAI Responses outputs with Bland AI, ensuring brand safety and compliance automatically.
What types of tasks can I perform by integrating OpenAI Responses with Bland AI?
Integrating OpenAI Responses with Bland AI allows you to perform various tasks, including:
- Automatically filtering out toxic or harmful content from AI-generated responses.
- Enhancing AI-driven customer service with real-time content moderation.
- Creating safer and more reliable AI applications for public use.
- Analyzing OpenAI-generated text for sentiment and potential biases.
- Building feedback loops to improve AI content quality continuously.
How to handle API key security for OpenAI Responses within Latenode?
Latenode provides secure storage and encryption for API keys. Use environment variables to manage credentials securely within your workflows.
Are there any limitations to the OpenAI Responses and Bland AI integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Bland AI's moderation accuracy depends on its model's training data.
- Rate limits on both OpenAI Responses and Bland AI APIs may impact workflow speed.
- Complex workflows with high data volumes may require optimization for performance.