Google Vertex AI and Qwilr Integration

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Google Vertex AI

Qwilr

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Google Vertex AI and Qwilr

Create a New Scenario to Connect Google Vertex AI and Qwilr

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

Add the Google Vertex AI Node

Select the Google Vertex AI node from the app selection panel on the right.

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Configure the Google Vertex AI

Click on the Google Vertex AI node to configure it. You can modify the Google Vertex AI 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 Qwilr Node

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

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Authenticate Qwilr

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

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

Most powerful ways to connect Google Vertex AI and Qwilr

Google Vertex AI + Qwilr + Slack: AI analyzes client data to generate a tailored proposal in Qwilr. A Slack notification is then sent to the sales team to inform them of the newly created proposal.

Qwilr + Google Vertex AI + HubSpot: When a proposal in Qwilr is accepted, trigger AI analysis to enrich the customer profile in HubSpot with relevant data.

Google Vertex AI and Qwilr integration alternatives

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.

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.

See how Latenode works

FAQ Google Vertex AI and Qwilr

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

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

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

Can I automatically generate Qwilr proposals using AI?

Yes, you can! Using Latenode, connect Google Vertex AI to Qwilr to create dynamic proposals. Generate personalized content with AI and automatically populate your Qwilr templates, saving time and improving conversions.

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

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

  • Automatically generate proposal drafts using AI based on customer data.
  • Personalize Qwilr proposals with AI-driven insights about client needs.
  • Use AI to optimize pricing suggestions within Qwilr proposals.
  • Automatically update Qwilr proposals based on real-time market data via AI.
  • Analyze proposal performance with AI to improve conversion rates.

Can I use Google Vertex AI to improve Qwilr proposal content?

Yes! Latenode lets you enhance Qwilr proposals with AI-generated text, improving clarity and persuasiveness with ease.

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

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

  • Complex AI models may require significant processing time.
  • Qwilr API rate limits may affect large-scale proposal generation.
  • Custom AI model deployment in Google Vertex AI requires technical expertise.

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