Connect airparser and Causal to Build Intelligent Automations

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airparser

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Causal

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Enable Integrations or automations with these events of airparser and Causal

Enable Integrations or automations with these events of airparser and Causal

Actions

Extract Document Data

Extract Document Data

Upload a document by URL to a selected Airparser inbox (PDF, image, DOCX, etc.), optionally include a custom filename and metadata, and return the extracted structured data.

Upload Document

Upload Document

Upload a file from a public URL to a selected Airparser inbox; optionally provide a custom filename and metadata.

List/Search Documents

List/Search Documents

List/Search Documents.

Fetch Document

Fetch Document

Retrieve a selected document.

Request a new Action for airparser

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Frequently Asked Questions

How do I start an integration between airparser and Causal?

To start, connect both your airparser and Causal accounts to viaSocket. Once connected, you can set up a workflow where an event in airparser triggers actions in Causal (or vice versa).

Can we customize how data from airparser is recorded in Causal?

Absolutely. You can customize how airparser data is recorded in Causal. This includes choosing which data fields go into which fields of Causal, setting up custom formats, and filtering out unwanted information.

How often does the data sync between airparser and Causal?

The data sync between airparser and Causal typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.

Can I filter or transform data before sending it from airparser to Causal?

Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.

Is it possible to add conditions to the integration between airparser and Causal?

Yes, you can set conditional logic to control the flow of data between airparser and Causal. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.

airparser

About airparser

Airparser is a GPT-powered data extraction tool. Extract structured data from PDFs, emails, HTML, texts, images and more.

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Causal

About Causal

Causal is a modern tool designed to simplify financial modeling, forecasting, and data analysis. It allows users to create dynamic models with ease, offering a more intuitive and collaborative approach to handling complex data. With Causal, users can connect their data sources, visualize outcomes, and share insights seamlessly, making it an ideal solution for businesses and individuals looking to enhance their decision-making processes.

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