Connect Tavily and kazm to Build Intelligent Automations

Choose a Trigger

Tavily

When this happens...

Choose an Action

kazm

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Enable Integrations or automations with these events of Tavily and kazm

Enable Integrations or automations with these events of Tavily and kazm

Actions

Search the web

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Search the web and return answers using Tavily.

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Frequently Asked Questions

How do I start an integration between Tavily and kazm?

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

Can we customize how data from Tavily is recorded in kazm?

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

How often does the data sync between Tavily and kazm?

The data sync between Tavily and kazm 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 Tavily to kazm?

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 Tavily and kazm?

Yes, you can set conditional logic to control the flow of data between Tavily and kazm. 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.

Tavily

About Tavily

Tavily is a comprehensive travel management platform designed to streamline the travel planning and booking process. It offers users a seamless experience in organizing trips, managing itineraries, and booking accommodations and transportation. With Tavily, users can access a wide range of travel options and services, ensuring a hassle-free travel experience.

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kazm

About kazm

Kazm is the data-driven CRM for Web3. We plug into every community touchpoint to create unified customer profiles, then apply machine learning and other methods to label, segment, and help personalize experiences for users.

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