Terms & concepts
Get acquainted with common terms related to conversational AI and your use of NLX
Common workspace terms & resources
APIs that trigger an outbound event and simply return a success or failure status
Custom or templated dashboards sharing key metrics for application performance, API performance, user engagement, and more
The conversational AI application that users interact with that is defined in your workspace by the channels and intents you assign it
The conversation method (voice, chat) and communication system (Amazon Connect, Twilio, etc.) your application uses to converse with users
Method for sharing information between intent flows in a single conversation session that can be statically set during a conversation's start or dynamically updated during the conversation
Displays a history of all conversation sessions with deployed applications that shows NLP information, including NLP confidence score and intent flows matched
APIs that return a response when invoked in an intent flow (e.g., hotel room availability, user name, movie showtimes)
A workflow constructed of multiple steps that defines the process for completing a business action to address a customer's intent
Intent
A customer's intent when interacting with a conversational AI application. Through provided training data, an AI model (NLP or LLM) can recognize intent and route to a particular flow from a user's utterance
Resource for creating a digital repository of knowledge that can answer common queries from users without the need to construct independent intents to address
APIs that represent extendable points in the conversation:
Conversation start
Escalation
Conversation end
Data request streaming (streams State modifications applied to Data requests when invoked in conversation)
Large Language Model; comprehends and generates human language responses from large deep learning models
Model Context Protocol is a standardized method for an MCP Client (supported LLM) to establish and communicate context to NLX and follow various tasks defined by NLX flows
Natural Language Processing (NLP); processes a user's lexical queries for matching to training data and slot values
Natural Language Understanding (NLU); built-into the NLX product, the NLU keeps track of conversation state and interfaces with backend and frontend services
Displays a list of all user utterances that had low NLP confidence scores or triggered the Unknown behavior
The training data provided to AI models to understand user intent and invoke the appropriate intent workflow
Sensitive or secret values, such as URL strings, API keys, passwords, etc
Slots are variables extracted from users that are required for completing a process outlined in an intent workflow. They may be matched to fixed values (custom), or open-ended (using the NLX system slots)
Multimodal conversation experiences that synchronize voice with externally-hosted digital assets
Utterances
User inputs that may be spoken or written
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