● Speech Recognition (STT): Google's speech-to-text technology, with a recognition rate of 97%.
● Speech Generation (TTS): text-to-speech technology.
● Parameter extraction (Slot Filling): technology that allows different variables to be identified in the same intention.
● Outgoing call campaigns: with the possibility of detecting voicemail and executing various actions, as appropriate.
● Virtual telephone numbers: from different countries.
● Duplex mode: interruption of the Virtual Assistant while giving a response.
● Inactivity trigger: messages sent to the user in case of inactivity to remind them to interact with the Virtual Assistant. If the user shows no activity, the call can be ended.
● Trigger for time out: messages sent to the user in case any API or service involved in the conversation takes longer than expected to respond.
● Silence Threshold: response time of the Virtual Assistant (configurable).
● Transfer to a human agent: complements the ability to transfer the conversation to a human agent when necessary.
● Emotion recognition: integrates sentiment analysis services to recognize the user's emotions and adapt the response based on that.
● Dynamic response generation: Create dynamic responses using variables and programming logic to customize Virtual Assistant interaction.
● Advanced Natural Language Processing (NLP): uses advanced NLP techniques to better understand the intentions and context of conversations.
● Conversation Analysis: incorporates conversation analysis tools to gain insights into user behavior and improve the Virtual Assistant experience.
● Contextual Personalization: adapts the Virtual Assistant's responses based on the context of the current conversation and the user's previous interactions.
● Branching scenarios: create conversations with multiple paths and options, allowing the user to take different routes based on their preferences.
● Context Tracking: keeps track of the context of the conversation to always provide consistent and relevant responses.
● Version Control: manage multiple versions of the Virtual Assistant for safe and controlled testing and deployment.
● Trend Analysis: uses data analysis to find trends and patterns in user conversations and adjust the Virtual Assistant accordingly.
The following items require Studio implementation. ● Integration with third-party services: connect the Virtual Assistant to external services to retrieve user-specific information or perform actions based on stored data.
● User Authentication: implements authentication methods to verify the user's identity before providing certain information or performing certain actions.
● Integration with CRM systems: integrate the Virtual Assistant with CRM systems to manage and record user interactions efficiently.
● Real-time update: allows the Virtual Assistant to update information in real time, for example, showing appointment availability or product inventory.
● Integration with payment platforms: allows the Virtual Assistant to carry out transactions and process payments securely by integrating it with recognized payment platforms.
● Data availability: being able to consult data from a conversation after referring to a human agent.