Pre-built Language Operators are Operators developed by Twilio in-house or trained using third-party AI models. This page covers the AI model used for training, Operator action, and supported languages for each of Twilio's Pre-built Operators.
The following Pre-built Language Operators are currently available:
| Name | AI model | Operator action | Description | Languages supported |
|---|---|---|---|---|
| Sentiment Analysis | OpenAI GPT-4o mini | Classify | Classifies call sentiment as positive, negative, neutral, or mixed | All |
| Summarization | OpenAI GPT-4o mini | Text generation | Creates a summary of the conversation | All |
| Entity Recognition | Amazon Comprehend | Classify-Extract | Identifies and extracts entities from the conversation | de-DE, en-AU, en-GB, en-US, es-MX, es-ES, es-US, fr-FR, it-IT, pt-BR, pt-PT |
| Agent Introduction | Twilio | Phrase matching | Detects if a participant introduced themselves during the conversation | en-AU, en-GB, en-US |
| Escalation Request | Twilio | Phrase matching | Detects if a participant requested an escalation during a conversation | en-AU, en-GB, en-US |
| Outbound Call Disposition | Twilio | Classify | Classifies the outcome of an outbound call | en-AU, en-GB, en-US |
| Recording Disclosure | Twilio | Phrase matching | Detects if a participant disclosed the call was recorded | en-AU, en-GB, en-US |
| Voicemail Detection | Twilio | Classify | Determines if a call went to voicemail or was answered by a human | en-AU, en-GB, en-US |
| Unavailable Party Detector | Twilio | Classify | Determines if the called party is unavailable | en-AU, en-GB, en-US |
| Do Not Contact Me | Twilio | Phrase matching | Detects if a participant requested not to be contacted | en-AU, en-GB, en-US |
| Non English Call | Twilio | Classify | Determines if the conversation is in English | en-AU, en-GB, en-US |
| Password Reset | Twilio | Phrase matching | Detects if a participant requested a password reset | en-AU, en-GB, en-US |
| Call Transfer | Twilio | Classify | Classifies if the call was transferred to another agent | en-AU, en-GB, en-US |
Action: Classify
Base Model: OpenAI GPT-4o mini
Approximately, the first 90,000 words of the transcript are used to evaluate the sentiment of the conversation.
The Sentiment Analysis operator evaluates the sentiment of the conversation. The Sentiment Analysis operator doesn't analyze a specific participant of the conversation.
| Class | Description |
|---|---|
positive | The sentiment of the call was positive |
negative | The sentiment of the call was negative |
neutral | The sentiment of the call was neutral |
mixed | There was more than one sentiment during the call |
Action: Text generation
Base Model: OpenAI GPT-4o mini
Approximately, the first 90,000 words of the transcript are used to create a summary highlighting key points and important information from the conversation.
The Summarization operator creates a summary highlighting key points and important information from the conversation.
Action: Classify-Extract
Base Model: Amazon Comprehend
The Entity Recognition operator identifies unique entities such as locations, organizations, consumer goods, people, quantities, and times.
| Entity | Description |
|---|---|
Person | Individuals, groups of people, nicknames, fictional characters |
Location | A specific location, such as a country, city, lake, building, etc. |
Organization | Large organizations, such as companies, government, sports teams, etc. |
Consumer_good | A branded product |
Date | A full date (10/20/1997), day (Wednesday), month (September), or time (10:15 AM.) |
Quantity | A quantified amount, such as currency, percentages, numbers, or bytes |
Action: Phrase matching
Base Model: Twilio
The Agent Introduction operator detects if an agent introduced themselves during a call.
The Agent Introduction operator doesn't detect a specific type of introduction. To determine whether an agent introduced themselves in a specific way, we recommend creating a Literal Spot operator that looks for the introductions that you are attempting to find.
| Class | Description |
|---|---|
true | The operator spotted an introduction |
false | The operator did not spot an introduction |
Action: Phrase matching
Base Model: Twilio
The Escalation Request operator detects if a customer requested an escalation during a call. It captures events like a customer asking to speak to a manager or a supervisor.
| Class | Description |
|---|---|
true | The operator spotted an escalation request |
false | The operator did not spot an escalation request |
Action: Classify
Base Model: Twilio
The Outbound Call Disposition operator categorizes the outcome of an outbound call. It's useful for customers who are running outbound dialing campaigns and have a set of outcomes that are focused on campaign list management.
| Class | Description |
|---|---|
GhostCall | The call was picked up and one participant does not provide any audio |
IVR | The call was picked up by an automated Interactive Voice Response (IVR) system |
NoContent | There was no audio during the call |
Ordinary | The call was picked up by a human and proceeded normally |
StopContactingMe | The call was picked up by a human who requested to be removed from a campaign list or requested to be placed on a do-not-call list |
Voicemail | The call was picked up by a voicemail system |
WrongNumber | The call was picked up by a human who indicated that it was a wrong number |
Action: Phrase matching
Base Model: Twilio
The Recording Disclosure operator detects if an agent informed the customer that the call was recorded. A typical use case for the Recording Disclosure operator is for outbound calls where a human agent should greet the customer before informing the customer that the call is being recorded.
The Recording Disclosure operator doesn't match a specific type of recording disclosure. If you have a specific disclosure that you want to ensure that agents use, we recommend creating a Literal Spot operator to match the required phrasing.
| Class | Description |
|---|---|
true | The operator spotted a participant mentioning that the call was being recorded |
false | The operator did not spot a participant mentioning that the call was being recorded |
Action: Classify
Base Model: Twilio
The Voicemail Detection operator identifies if a call went to voicemail. It's useful for customers who are running outbound dialing campaigns and want to use the results to determine whether to call a specific customer back, and to assess the best time to make that call.
Unlike the Outbound Call Disposition operator, the Voicemail Detection operator only indicates whether a call was handed to a voicemail system. It does not use acoustic features to determine whether or not the call was actually picked up by the voicemail system.
| Class | Description |
|---|---|
voicemail | The call was picked up by a voicemail system |
not_voicemail | The call was not picked up by a voicemail system |
Action: Phrase matching
Base Model: Twilio
The Do Not Contact Me operator detects if a customer requested not to be contacted during a call.
| Class | Description |
|---|---|
true | Customer requested to stop contacting this number |
false | Customer did not request to stop contacting this number |
Action: Classify
Base Model: Twilio
The Non English Call operator identifies if the conversation was in English.
| Class | Description |
|---|---|
NonEnglishCall | Participants spoke in a non-English language |
EnglishCall | Participants spoke in English |
Action: Classify
Base Model: Twilio
The Password Reset operator detects if a call participant requested a password reset.
| Class | Description |
|---|---|
NoPasswordReset | Password Reset was not requested |
PasswordReset | Password Reset was requested |
Action: Classify
Base Model: Twilio
The Call Transfer operator identifies if the call was transferred.
| Class | Description |
|---|---|
NoTransfer | The call was not transferred |
Transfer | The call was transferred |
To understand how to use Pre-built Language Operators on your Voice Intelligence Service, please visit the following resources: