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

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

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

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Authenticate Google Cloud Storage
Now, click the Google Cloud Storage node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Google Cloud Storage settings. Authentication allows you to use Google Cloud Storage through Latenode.
Configure the OCR Space and Google Cloud Storage 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 OCR Space and Google Cloud Storage 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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Trigger on Webhook
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Save and Activate the Scenario
After configuring OCR Space, Google Cloud Storage, 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 OCR Space and Google Cloud Storage integration works as expected. Depending on your setup, data should flow between OCR Space and Google Cloud Storage (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect OCR Space and Google Cloud Storage
Google Cloud Storage + OCR Space + Google Docs: When a new file is uploaded to a Google Cloud Storage bucket, the file's text is extracted using OCR Space. Then, a new Google Docs document is created using the extracted text.
Google Cloud Storage + OCR Space + Slack: When a new file is uploaded to a Google Cloud Storage bucket, OCR Space extracts the text from the image or PDF. The extracted text is then sent to a specified Slack channel.
OCR Space and Google Cloud Storage integration alternatives
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.
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About Google Cloud Storage
Use Google Cloud Storage in Latenode for automated file management. Upload, download, and manage files in your workflows. Automate backups, data archiving, or image processing. Connect GCS to other apps for seamless data transfer and triggering events. Latenode's visual editor simplifies complex file-based automations.
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See how Latenode works
FAQ OCR Space and Google Cloud Storage
How can I connect my OCR Space account to Google Cloud Storage using Latenode?
To connect your OCR Space account to Google Cloud Storage on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select OCR Space and click on "Connect".
- Authenticate your OCR Space and Google Cloud Storage accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automatically process invoices and store them in the cloud?
Yes, you can! Latenode's visual editor makes it easy to build automations for processing invoices with OCR Space and archiving them in Google Cloud Storage. Benefit from efficient document management.
What types of tasks can I perform by integrating OCR Space with Google Cloud Storage?
Integrating OCR Space with Google Cloud Storage allows you to perform various tasks, including:
- Automatically extract text from scanned documents and store them in GCS.
- Process receipts and archive the data in a structured format within GCS.
- Create searchable archives of image-based PDFs using OCR and cloud storage.
- Monitor a GCS bucket for new images and trigger OCR processing automatically.
- Back up OCR Space processed text files to a secure Google Cloud Storage bucket.
How do I handle large volumes of documents using OCR Space on Latenode?
Latenode's scaling features enable efficient processing of large document volumes. You can also use JavaScript for custom error handling.
Are there any limitations to the OCR Space and Google Cloud Storage integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- OCR Space's API usage limits may affect the number of documents processed.
- Large files can take time to process due to API response times.
- Complex document layouts may require fine-tuning for optimal text extraction.