Connect Groq and kazm to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for Groq
Choose an Action
Automatically do this!
- Request a new Action for kazm
Enable Integrations or automations with these events of Groq and kazm
Enable Integrations or automations with these events of Groq and kazm
Actions
Create chat completion
Creates a model response for the given chat conversation.
List models
List all available models.
Create transcription
Transcribes audio into the input language.
Retrieve model
Get detailed information about a model.
List batch
List your organization's batches.
Ask AI
Ask any Question using a model.
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Frequently Asked Questions
To start, connect both your Groq and kazm accounts to viaSocket. Once connected, you can set up a workflow where an event in Groq triggers actions in kazm (or vice versa).
Absolutely. You can customize how Groq 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.
The data sync between Groq and kazm typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between Groq 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.
About Groq
GroqCloud is a cutting-edge platform designed to enhance computational efficiency and performance. It leverages advanced technology to provide high-speed processing capabilities, making it ideal for businesses and developers looking to optimize their computational tasks. With GroqCloud, users can experience accelerated data processing, enabling faster decision-making and improved productivity.
Learn MoreAbout 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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