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Automatically extract data from documents processed in Docparser and send it directly to Lark for streamlined data entry and reporting. Latenode's visual editor makes setup simple, and affordable execution-based pricing saves money as your automation scales.
Connect Docparser and Lark in minutes with Latenode.
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In the workspace, click the “Create New Scenario” button.

Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Docparser, triggered by another scenario, or executed manually (for testing purposes). In most cases, Docparser or Lark will be your first step. To do this, click "Choose an app," find Docparser or Lark, and select the appropriate trigger to start the scenario.

Select the Docparser node from the app selection panel on the right.

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

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Lark
Now, click the Lark node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Lark settings. Authentication allows you to use Lark through Latenode.
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Use various Latenode nodes to transform data and enhance your integration:

JavaScript
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AI Anthropic Claude 3
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Lark
Trigger on Webhook
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Docparser
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Iterator
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Webhook response
After configuring Docparser, Lark, 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.
Run the scenario by clicking “Run once” and triggering an event to check if the Docparser and Lark integration works as expected. Depending on your setup, data should flow between Docparser and Lark (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Docparser + Lark + Google Sheets: When a document is parsed in Docparser, extract the relevant data and update employee records in Lark by finding the user. Then, add a new row to a Google Sheet to track these updates.
Lark + Docparser + Airtable: When a new message is received in a Lark group chat (acting as a form submission), upload the message content or a linked document to Docparser for parsing. The parsed data is then structured and stored as a new record in Airtable.
About Docparser
Extract data from PDFs, invoices, and forms automatically with Docparser in Latenode. Stop manual data entry. Build workflows that trigger actions based on parsed content. Use Latenode’s no-code tools to filter, transform, and route data to your database or apps, creating scalable document processing pipelines.
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About Lark
Use Lark within Latenode to centralize team comms & automate notifications based on workflow triggers. Aggregate messages, streamline approvals, and post updates to specific channels. Benefit from Latenode's visual editor and logic tools for advanced routing that keeps everyone informed and aligned.
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How can I connect my Docparser account to Lark using Latenode?
To connect your Docparser account to Lark on Latenode, follow these steps:
Can I automatically update Lark with parsed invoice data?
Yes, with Latenode! Automatically send parsed data from Docparser to Lark, streamlining your financial reporting. Latenode's visual editor makes complex workflows simple.
What types of tasks can I perform by integrating Docparser with Lark?
Integrating Docparser with Lark allows you to perform various tasks, including:
How does Latenode handle errors during Docparser data extraction?
Latenode provides robust error handling. You can set up alerts and automatically retry failed Docparser data extractions for guaranteed accuracy.
Are there any limitations to the Docparser and Lark integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of: