OCR Space and Streamtime Integration

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Automatically extract invoice data from OCR Space and log billable hours in Streamtime. Latenode's visual editor makes customization simple, letting you integrate custom logic and scale affordably without extra fees.

Swap Apps

OCR Space

Streamtime

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect OCR Space and Streamtime

Create a New Scenario to Connect OCR Space and Streamtime

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 Streamtime will be your first step. To do this, click "Choose an app," find OCR Space or Streamtime, 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.

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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.

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OCR Space

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Connect OCR Space

Sign In

Run node once

Add the Streamtime Node

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

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Streamtime

Authenticate Streamtime

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

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OCR Space

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Streamtime

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Connect Streamtime

Sign In

Run node once

Configure the OCR Space and Streamtime 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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Streamtime Oauth 2.0

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The action ID

Run node once

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

OCR Space + Streamtime + Google Drive: When a new file is added to a specific Google Drive folder, OCR Space extracts the invoice data from the image. This data is then used to create a new job in Streamtime, and the original file is moved to a designated archive folder in Google Drive.

Streamtime + OCR Space + QuickBooks: When a job is completed in Streamtime, the automation searches for receipts in Google Drive using keywords from the Streamtime job. OCR Space extracts the expense data from these receipts and creates a new invoice in QuickBooks.

OCR Space and Streamtime 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.

About Streamtime

Streamtime project management inside Latenode: automate tasks like invoice creation based on project status, or sync time entries with accounting. Connect Streamtime to other apps via Latenode's visual editor and AI tools. Customize further with JavaScript for complex workflows. Manage projects and data automatically.

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FAQ OCR Space and Streamtime

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

To connect your OCR Space account to Streamtime 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 Streamtime accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I automatically create Streamtime projects from scanned invoices?

Yes! Latenode lets you use OCR Space to extract data from invoices, then create corresponding projects in Streamtime, saving time and ensuring accurate project setup.

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

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

  • Automatically creating Streamtime tasks from text in scanned documents.
  • Updating project details in Streamtime using OCR Space data.
  • Extracting invoice amounts and logging them as expenses in Streamtime.
  • Populating Streamtime client information from scanned business cards.
  • Triggering project status updates in Streamtime based on OCR data analysis.

How does Latenode enhance OCR Space data processing?

Latenode adds advanced logic, AI, and JavaScript code to clean and format OCR Space results before sending it to Streamtime.

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

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

  • OCR Space accuracy depends on the quality of the scanned documents.
  • Streamtime's API rate limits might affect high-volume data processing.
  • Complex document layouts may require custom JavaScript pre-processing.

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