Qwilr and Google Vertex AI Integration

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Use Qwilr data to train Google Vertex AI models on Latenode, improving proposal win rates with custom AI. Benefit from no-code flexibility and scale affordably by paying only for execution time.

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Qwilr

Google Vertex AI

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Qwilr and Google Vertex AI

Create a New Scenario to Connect Qwilr and Google Vertex AI

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 Qwilr, triggered by another scenario, or executed manually (for testing purposes). In most cases, Qwilr or Google Vertex AI will be your first step. To do this, click "Choose an app," find Qwilr or Google Vertex AI, and select the appropriate trigger to start the scenario.

Add the Qwilr Node

Select the Qwilr node from the app selection panel on the right.

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Qwilr

Configure the Qwilr

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

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Run node once

Add the Google Vertex AI Node

Next, click the plus (+) icon on the Qwilr node, select Google Vertex AI from the list of available apps, and choose the action you need from the list of nodes within Google Vertex AI.

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Google Vertex AI

Authenticate Google Vertex AI

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

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Configure the Qwilr and Google Vertex AI 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 Qwilr and Google Vertex 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 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 Qwilr, Google Vertex AI, 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 Qwilr and Google Vertex AI integration works as expected. Depending on your setup, data should flow between Qwilr and Google Vertex AI (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.

Most powerful ways to connect Qwilr and Google Vertex AI

Qwilr + Google Vertex AI + Slack: When a Qwilr page is viewed, the content is analyzed by Google Vertex AI for sentiment. If the sentiment is negative, a notification is sent to a Slack channel to alert the sales team.

Qwilr + Google Vertex AI + Google Sheets: When a Qwilr page is accepted, its content is summarized using Google Vertex AI. The summary and relevant details are then added as a new row in Google Sheets for tracking proposal outcomes.

Qwilr and Google Vertex AI integration alternatives

About Qwilr

Automate Qwilr quote creation inside Latenode workflows. Automatically generate Qwilr proposals when triggered by new CRM leads or form submissions. Send data to Qwilr, then use Latenode to track views, trigger follow-ups, and update your database—no manual data entry needed. Scale personalized sales flows with ease.

About Google Vertex AI

Use Vertex AI in Latenode to build AI-powered automation. Quickly integrate machine learning models for tasks like sentiment analysis or image recognition. Automate data enrichment or content moderation workflows without complex coding. Latenode’s visual editor makes it easier to chain AI tasks and scale them reliably, paying only for the execution time of each flow.

See how Latenode works

FAQ Qwilr and Google Vertex AI

How can I connect my Qwilr account to Google Vertex AI using Latenode?

To connect your Qwilr account to Google Vertex AI on Latenode, follow these steps:

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

Can I automatically summarize client feedback from Qwilr proposals?

Yes, you can! Latenode lets you send Qwilr data to Google Vertex AI for instant summarization. Streamline insights from client interactions automatically and focus on high-value tasks.

What types of tasks can I perform by integrating Qwilr with Google Vertex AI?

Integrating Qwilr with Google Vertex AI allows you to perform various tasks, including:

  • Generate personalized proposal introductions using AI.
  • Automatically extract key client requirements from Qwilr responses.
  • Create custom follow-up messages based on proposal feedback.
  • Enhance Qwilr proposals with AI-powered data analysis.
  • Automate client segmentation based on proposal interactions.

Can I use custom JavaScript functions with Qwilr on Latenode?

Yes, Latenode supports custom JavaScript functions. Extend Qwilr's capabilities with custom logic, data transformations, and dynamic workflows tailored to your specific needs.

Are there any limitations to the Qwilr and Google Vertex AI integration on Latenode?

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

  • Large data volumes may impact processing speed.
  • Custom AI models require appropriate setup in Google Vertex AI.
  • Qwilr API rate limits can affect workflow execution frequency.

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