– Production: https://api.callease.ai/api/v1
All endpoints require Bearer token authentication:
Authorization: Bearer <API KEY>
Make a Call
POST /calls
Create a new outbound call.
Request Body:
{
"assistant_id": "id",
"name": "string",
"phoneNumber": "string",
"customVariables": [
{
"key": "string",
"value": "string"
}
]
}
Example Request:
{
"assistant_id": "CE_3228070481",
"name": "John",
"phoneNumber": "+123456789",
"customVariables": [
{
"key": "name",
"value": "John"
},
{
"key": "cal_email",
"value": "abc@email.com"
}
]
}
Get Call Details
GET /calls
Retrieve call details.
Response: Returns call information in JSON format.
Base URL: https://api.callease.ai/api/v1
All endpoints require Bearer token authentication.
Create Action
POST /actions
Create a new action with SMS capabilities.
Request Body:
{
"SEND_SMS": {
"content": "message content",
"instructions": "message instructions"
}
}
List Actions
GET /actions
Retrieve a list of all actions.
Get Actions
GET /actions/{action_id}
Get details of a specific action.
Update Actions
PUT /actions/{action_id}
Update an existing action.
Request Body:
{
"SEND_SMS": {
"content": "SMS CONTENT HERE",
"instructions": "SMS CONDITION HERE"
}
}
Delete Actions
DELETE /actions/{action_id}
Delete a specific action.
Attach Actions
POST /actions/attach
Attach actions to an assistant.
Request Body:
{
"assistant_id": "assistant-d",
"actions": [
"action-id"
]
}
Dettach Actions
POST /actions/detach
Detach actions from an assistant.
{
"assistant_id": "assistant-id",
"actions": [
"action-id-1",
"action-id-2"
]
}
This document outlines the security practices and data handling measures implemented in Callease.ai, which uses third-party services, Large Language Models (LLM), and third-party VoIP services (such as Twilio), and is hosted on trusted third-party cloud service. The goal is to ensure that data privacy, security, and compliance are maintained throughout the system architecture.
Callease.ai is designed to provide users with conversational AI capabilities. The system integrates multiple third-party services, including:
The data flowing through the system is handled with the utmost security. This document specifies how data is handled, processed, stored, and protected throughout the web application’s architecture.
Callease.ai collects several types of data from users and systems:
Data retention policies vary by data type:
Data collected is kept to the minimum necessary for the system’s operations. Personal and sensitive data is only processed when explicitly required for functionality (e.g., sending a voice message via Twilio or customizing conversational AI responses).
As we’ve fine-tuned a third-party LLM, input data may be transmitted to and processed by the third-party models. To ensure privacy:
Callease.ai integrates with Twilio to enable voice, messaging, and communication features. Twilio handles communication data (e.g., phone numbers, text messages, voice recordings), and security measures are as follows:
Trusted Third-Party Cloud Service is used for hosting and managing the backend of the web application. The security measures in place include:
Encryption in Transit: All data exchanged between users, third-party services (e.g., Twilio, LLM), and the Cloud services is encrypted using TLS 1.2 or higher.
Before collecting any personal or sensitive data, users are informed about the data collection and its purpose. Consent is obtained where required, and users are provided with options to manage their preferences.
Users can:
In case of a data breach or security incident:
Callease.ai is designed with strong security and data protection practices, utilizing industry standards for encryption, access control, and data minimization. By integrating with third-party services like LLMs, Twilio, and trusted cloud services, the system ensures that data is processed securely while maintaining compliance with privacy regulations.
This document serves as a comprehensive guide to the data handling and security policies implemented within the Callease.ai. Regular security audits and reviews will be conducted to ensure that data protection practices are up-to-date and effective.
– Production: https://api.callease.ai/api/v1
All endpoints require Bearer token authentication:
Authorization: Bearer <API KEY>
Make a Call
POST /calls
Create a new outbound call.
Request Body:
{
"assistant_id": "id",
"name": "string",
"phoneNumber": "string",
"customVariables": [
{
"key": "string",
"value": "string"
}
]
}
Example Request:
{
"assistant_id": "CE_3228070481",
"name": "John",
"phoneNumber": "+123456789",
"customVariables": [
{
"key": "name",
"value": "John"
},
{
"key": "cal_email",
"value": "abc@email.com"
}
]
}
Get Call Details
GET /calls
Retrieve call details.
Response: Returns call information in JSON format.
Base URL: https://api.callease.ai/api/v1
All endpoints require Bearer token authentication.
Create Action
POST /actions
Create a new action with SMS capabilities.
Request Body:
{
"SEND_SMS": {
"content": "message content",
"instructions": "message instructions"
}
}
List Actions
GET /actions
Retrieve a list of all actions.
Get Actions
GET /actions/{action_id}
Get details of a specific action.
Update Actions
PUT /actions/{action_id}
Update an existing action.
Request Body:
{
"SEND_SMS": {
"content": "SMS CONTENT HERE",
"instructions": "SMS CONDITION HERE"
}
}
Delete Actions
DELETE /actions/{action_id}
Delete a specific action.
Attach Actions
POST /actions/attach
Attach actions to an assistant.
Request Body:
{
"assistant_id": "assistant-d",
"actions": [
"action-id"
]
}
Dettach Actions
POST /actions/detach
Detach actions from an assistant.
{
"assistant_id": "assistant-id",
"actions": [
"action-id-1",
"action-id-2"
]
}
This document outlines the security practices and data handling measures implemented in Callease.ai, which uses third-party services, Large Language Models (LLM), and third-party VoIP services (such as Twilio), and is hosted on trusted third-party cloud service. The goal is to ensure that data privacy, security, and compliance are maintained throughout the system architecture.
Callease.ai is designed to provide users with conversational AI capabilities. The system integrates multiple third-party services, including:
The data flowing through the system is handled with the utmost security. This document specifies how data is handled, processed, stored, and protected throughout the web application’s architecture.
Callease.ai collects several types of data from users and systems:
Data retention policies vary by data type:
Data collected is kept to the minimum necessary for the system’s operations. Personal and sensitive data is only processed when explicitly required for functionality (e.g., sending a voice message via Twilio or customizing conversational AI responses).
As we’ve fine-tuned a third-party LLM, input data may be transmitted to and processed by the third-party models. To ensure privacy:
Callease.ai integrates with Twilio to enable voice, messaging, and communication features. Twilio handles communication data (e.g., phone numbers, text messages, voice recordings), and security measures are as follows:
Trusted Third-Party Cloud Service is used for hosting and managing the backend of the web application. The security measures in place include:
Encryption in Transit: All data exchanged between users, third-party services (e.g., Twilio, LLM), and the Cloud services is encrypted using TLS 1.2 or higher.
Before collecting any personal or sensitive data, users are informed about the data collection and its purpose. Consent is obtained where required, and users are provided with options to manage their preferences.
Users can:
In case of a data breach or security incident:
Callease.ai is designed with strong security and data protection practices, utilizing industry standards for encryption, access control, and data minimization. By integrating with third-party services like LLMs, Twilio, and trusted cloud services, the system ensures that data is processed securely while maintaining compliance with privacy regulations.
This document serves as a comprehensive guide to the data handling and security policies implemented within the Callease.ai. Regular security audits and reviews will be conducted to ensure that data protection practices are up-to-date and effective.
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