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

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

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Configure the FreshBooks
Click on the FreshBooks node to configure it. You can modify the FreshBooks URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the Google Vertex AI Node
Next, click the plus (+) icon on the FreshBooks 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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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.
Configure the FreshBooks 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.
Set Up the FreshBooks 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 FreshBooks, 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 FreshBooks and Google Vertex AI integration works as expected. Depending on your setup, data should flow between FreshBooks 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 FreshBooks and Google Vertex AI
FreshBooks + Google Vertex AI + Slack: When a new invoice is created in FreshBooks, the description is sent to Google Vertex AI to categorize the expense. The categorization is then sent to a designated Slack channel to notify the accounting team.
FreshBooks + Google Vertex AI + Google Sheets: This automation uses FreshBooks customer data to send payment information to Google Vertex AI. AI predicts late payments, then logs the prediction results and the FreshBooks customer ID into a Google Sheet for tracking and analysis.
FreshBooks and Google Vertex AI integration alternatives
About FreshBooks
Connect FreshBooks to Latenode to automate invoice creation and payment tracking. Trigger actions in other apps (CRM, email) based on FreshBooks events. Centralize accounting data into workflows, use AI to analyze spendings, and get custom notifications – all automated with Latenode's flexible, no-code visual builder.
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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.
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See how Latenode works
FAQ FreshBooks and Google Vertex AI
How can I connect my FreshBooks account to Google Vertex AI using Latenode?
To connect your FreshBooks account to Google Vertex AI on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select FreshBooks and click on "Connect".
- Authenticate your FreshBooks and Google Vertex AI accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automatically categorize FreshBooks expenses using AI?
Yes, you can! Latenode lets you send FreshBooks expense data to Google Vertex AI for analysis, then update the expense category automatically. Save time and improve accuracy with AI-powered automation.
What types of tasks can I perform by integrating FreshBooks with Google Vertex AI?
Integrating FreshBooks with Google Vertex AI allows you to perform various tasks, including:
- Automatically extracting invoice data for AI-driven forecasting.
- Analyzing customer feedback from FreshBooks projects with AI.
- Generating personalized invoice summaries using AI models.
- Identifying potential payment delays using predictive AI analysis.
- Automating expense categorization with AI-powered text analysis.
How to trigger workflows based on FreshBooks invoice status changes?
Use Latenode's FreshBooks trigger to monitor invoice status changes. Then, automatically send data to Google Vertex AI for analysis or action using our no-code editor.
Are there any limitations to the FreshBooks and Google Vertex AI integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Complex AI models may require advanced configuration in Google Vertex AI.
- Rate limits on the FreshBooks API may affect high-volume data processing.
- Custom data mapping may be needed for specialized AI processing.