Connect Leadsquared and AI/ML API to Build Intelligent Automations
Enable Integrations or automations with these events of Leadsquared and AI/ML API
Enable Integrations or automations with these events of Leadsquared and AI/ML API
Actions
Create a new lead
Create a lead in LeadSquared
Find a lead by email id
Find a lead using email id
Find Lead by Phone
Retrieve leads that match one or more phone numbers. Optionally select which lead fields to return.
Create activity on a lead
Post an Activity on a Lead
Search Lead by Criteria
Search lead by criteria
Search Leads by Date
Retrieve leads modified between a start and end date, returning selected fields with optional sorting and pagination.
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Frequently Asked Questions
To start, connect both your Leadsquared and AI/ML API accounts to viaSocket. Once connected, you can set up a workflow where an event in Leadsquared triggers actions in AI/ML API (or vice versa).
Absolutely. You can customize how Leadsquared data is recorded in AI/ML API. This includes choosing which data fields go into which fields of AI/ML API, setting up custom formats, and filtering out unwanted information.
The data sync between Leadsquared and AI/ML API 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 Leadsquared and AI/ML API. 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 Leadsquared
Leadsquared is a comprehensive marketing automation and CRM platform designed to help businesses streamline their lead management, sales automation, and customer engagement processes.
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About AI/ML API
AI/ML API provides advanced artificial intelligence and machine learning capabilities to developers and businesses, enabling them to integrate intelligent features into their applications. With a wide range of AI models and tools, users can enhance their software with capabilities such as natural language processing, image recognition, predictive analytics, and more.
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