Amazon S3 and OCR Space Integration

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Automatically process documents: Extract text from images stored in Amazon S3 using OCR Space, then use Latenode's visual editor to build custom logic, transform data, and scale affordably without complex coding.

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Amazon S3

OCR Space

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Amazon S3 and OCR Space

Create a New Scenario to Connect Amazon S3 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 Amazon S3, triggered by another scenario, or executed manually (for testing purposes). In most cases, Amazon S3 or OCR Space will be your first step. To do this, click "Choose an app," find Amazon S3 or OCR Space, and select the appropriate trigger to start the scenario.

Add the Amazon S3 Node

Select the Amazon S3 node from the app selection panel on the right.

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Amazon S3

Configure the Amazon S3

Click on the Amazon S3 node to configure it. You can modify the Amazon S3 URL and choose between DEV and PROD versions. You can also copy it for use in further automations.

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Sign In

Run node once

Add the OCR Space Node

Next, click the plus (+) icon on the Amazon S3 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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OCR Space

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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OCR Space

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Configure the Amazon S3 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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OCR Space Oauth 2.0

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The action ID

Run node once

Set Up the Amazon S3 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 Amazon S3, 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 Amazon S3 and OCR Space integration works as expected. Depending on your setup, data should flow between Amazon S3 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 Amazon S3 and OCR Space

Amazon S3 + OCR Space + Google Sheets: When a new file is added to an Amazon S3 bucket, the file (presumably an invoice) is sent to OCR Space to extract the text. Then, the extracted text data is added as a new row in a Google Sheets spreadsheet for accounting purposes.

OCR Space + Amazon S3 + Slack: When OCR Space converts a scanned document into text, the resulting text file is stored in an Amazon S3 bucket. After the file is uploaded to S3, a message is sent to a designated Slack channel to notify users that the conversion is complete and the file is available.

Amazon S3 and OCR Space integration alternatives

About Amazon S3

Automate S3 file management within Latenode. Trigger flows on new uploads, automatically process stored data, and archive old files. Integrate S3 with your database, AI models, or other apps. Latenode simplifies complex S3 workflows with visual tools and code options for custom logic.

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 Amazon S3 and OCR Space

How can I connect my Amazon S3 account to OCR Space using Latenode?

To connect your Amazon S3 account to OCR Space on Latenode, follow these steps:

  • Sign in to your Latenode account.
  • Navigate to the integrations section.
  • Select Amazon S3 and click on "Connect".
  • Authenticate your Amazon S3 and OCR Space accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I automatically process invoices stored in Amazon S3 using OCR Space?

Yes, you can. Latenode's visual editor makes this easy; automatically extract invoice data and store it in a database—saving time and reducing manual data entry errors.

What types of tasks can I perform by integrating Amazon S3 with OCR Space?

Integrating Amazon S3 with OCR Space allows you to perform various tasks, including:

  • Automatically extract text from scanned documents stored in Amazon S3.
  • Create searchable PDFs from image files archived in Amazon S3.
  • Process receipts stored in Amazon S3 for expense reporting.
  • Monitor an Amazon S3 bucket and process new image files as they arrive.
  • Archive processed documents back to Amazon S3 for long-term storage.

How does Latenode handle large files stored in Amazon S3 for OCR processing?

Latenode efficiently handles large files by streaming data, avoiding memory issues and enabling scalable processing of large Amazon S3 documents.

Are there any limitations to the Amazon S3 and OCR Space integration on Latenode?

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

  • OCR Space has rate limits on the number of API calls per hour.
  • The accuracy of OCR depends on the quality of the scanned documents.
  • Very large files may require significant processing time.

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