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Automate SMS data entry by using OCR Space to extract text from images and then sending it via Sinch. Latenode simplifies data transformations with visual no-code tools and allows custom logic with JavaScript for complex parsing, all at an affordable pay-as-you-go rate.
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Create a New Scenario to Connect Sinch 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 Sinch, triggered by another scenario, or executed manually (for testing purposes). In most cases, Sinch or OCR Space will be your first step. To do this, click "Choose an app," find Sinch or OCR Space, and select the appropriate trigger to start the scenario.
Add the Sinch Node
Select the Sinch node from the app selection panel on the right.
Sinch
Add the OCR Space Node
Next, click the plus (+) icon on the Sinch node, select OCR Space from the list of available apps, and choose the action you need from the list of nodes within OCR Space.
Sinch
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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.
Configure the Sinch 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.
Set Up the Sinch and OCR Space Integration
Use various Latenode nodes to transform data and enhance your integration:
JavaScript
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AI Anthropic Claude 3
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OCR Space
Trigger on Webhook
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Sinch
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Iterator
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Webhook response
Save and Activate the Scenario
After configuring Sinch, 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 Sinch and OCR Space integration works as expected. Depending on your setup, data should flow between Sinch and OCR Space (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Sinch + OCR Space + Google Sheets: When a new SMS containing an image arrives in Sinch, the image is processed by OCR Space to extract the text. This extracted text is then added as a new row in a Google Sheets spreadsheet.
OCR Space + Sinch + Twilio: When an image is converted to text using OCR Space, the resulting text is sent via SMS using Twilio to a specified phone number. The image can be triggered by an action in Sinch, for example.
About Sinch
Use Sinch in Latenode to automate SMS tasks. Send messages for order updates, appointment reminders, or two-factor authentication directly from your workflows. Benefit from Latenode's visual editor to easily integrate Sinch with other apps. Scale communication tasks without complex coding or expensive per-step pricing.
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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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How can I connect my Sinch account to OCR Space using Latenode?
To connect your Sinch account to OCR Space on Latenode, follow these steps:
Can I extract text from images sent via Sinch SMS?
Yes, you can. Latenode simplifies this by automating image processing and data extraction, turning message attachments into actionable data. This saves time and reduces manual data entry.
What types of tasks can I perform by integrating Sinch with OCR Space?
Integrating Sinch with OCR Space allows you to perform various tasks, including:
How do I handle large volumes of Sinch messages efficiently in Latenode?
Latenode’s architecture scales to handle high message volumes, ensuring efficient processing through parallel execution and optimized resource allocation.
Are there any limitations to the Sinch and OCR Space integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of: