Google Vertex AI and OCR Space Integration

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Automatically extract text from scanned documents using OCR Space, then leverage Google Vertex AI for analysis and classification. Build this enhanced document processing pipeline in Latenode's visual editor, customizing every step with JavaScript and scaling affordably.

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Google Vertex AI

OCR Space

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Google Vertex AI and OCR Space

Create a New Scenario to Connect Google Vertex AI and OCR Space

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 OCR Space will be your first step. To do this, click "Choose an app," find Google Vertex AI or OCR Space, 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 OCR Space Node

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

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Authenticate OCR Space

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

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Configure the Google Vertex AI and OCR Space 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 Google Vertex AI and OCR Space 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, OCR Space, 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 OCR Space integration works as expected. Depending on your setup, data should flow between Google Vertex AI and OCR Space (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 OCR Space

OCR Space + Google Vertex AI + Google Sheets: When a new image is uploaded, OCR Space extracts the text. Google Vertex AI analyzes the extracted text, and the insights are then logged into a Google Sheet.

Slack + OCR Space + Google Vertex AI: When a new file is added to Slack, OCR Space extracts text from the image. Google Vertex AI analyzes the sentiment of the extracted text. If the sentiment is negative, an alert is sent to a specified Slack channel.

Google Vertex AI and OCR Space 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 OCR Space

Need to extract text from images or PDFs? Use OCR Space in Latenode to automatically process documents and integrate the data into your workflows. Automate invoice processing, data entry, or compliance checks. Latenode adds flexible logic, file parsing, and destinations to your OCR results, scaling beyond single-document processing.

See how Latenode works

FAQ Google Vertex AI and OCR Space

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

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

  • Sign in to your Latenode account.
  • Navigate to the integrations section.
  • Select Google Vertex AI and OCR Space, then click "Connect".
  • Authenticate your accounts, granting the necessary permissions.
  • Start building automated workflows with both apps.

Can I automatically classify scanned documents using AI?

Yes, you can! Latenode enables seamless integration, allowing you to extract text with OCR Space and then use Google Vertex AI to classify and route documents automatically.

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

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

  • Automatically processing and classifying invoices.
  • Extracting data from images for analysis.
  • Classifying support tickets using OCRed text.
  • Automating document verification workflows.
  • Analyzing sentiment from scanned text.

How does Latenode simplify Google Vertex AI integration?

Latenode provides a visual interface, pre-built components, and easy authentication, making Google Vertex AI integration simple and fast, even without coding.

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

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

  • Large volumes of OCR processing may require an upgraded OCR Space plan.
  • Google Vertex AI model training and deployment are separate processes.
  • Complex document layouts may require adjustments for optimal OCR accuracy.

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