Assistants

Topic	Detail
Navigation	Admin → Contact Center → Assistants
Purpose	AI-powered virtual agents (bots) using NLU to handle voice and digital interactions automatically
Technology	Natural Language Understanding (NLU)
Integration	Works with Knowledge Base and Architect flows

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Overview

Assistants are AI-powered automation tools that enable organizations to build virtual agents capable of interacting with customers through voice and digital channels. They use Natural Language Understanding (NLU) to interpret customer requests and respond using knowledge articles, intents, and Architect flows.

Assistants are most effective for automating predictable, repetitive interactions — reducing call volume, improving self-service, and lowering operational costs.

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Assistant Components

Component	Description
Intents	The goal or purpose of the customer's request (e.g., Check_Order_Status, Reset_Password)
Utterances	Example phrases customers might say to express an intent — used to train the NLU model
Entities	Variables extracted from customer input (e.g., order number, city, product name)
Slots	Structured data fields collected during a conversation to fulfill an intent
Actions	Responses or operations the assistant performs when an intent is matched
Knowledge Integration	Allows the assistant to answer questions directly from knowledge base articles
Architect Flow Integration	Transfers conversation control to an Architect flow for advanced routing or logic

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Configuration Settings

Option	Description
Language	NLU processing language — determines which utterance model is used
Confidence Threshold	Minimum confidence score required to trigger an intent — below this, fallback intent fires
Fallback Intent	Default action when no intent is recognized (e.g., transfer to agent)
Disambiguation	Prompts the customer to clarify when multiple intents closely match

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Example Assistant Flow

Customer: "I want to check my order status"
       ↓
Intent Detected: Order_Status
       ↓
Extract Entity: Order_Number
       ↓
Call API via Data Action / Architect Flow
       ↓
Return Response to Customer
       ↓
(If unresolved) Escalate to Human Agent

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Best Use Scenarios

Scenario	Description
Customer Self-Service	Resolve common issues without agent involvement
FAQ Automation	Answer frequently asked questions automatically using knowledge articles
Order / Account Status	Retrieve order status, balance, or appointment info via API
Call Routing by Intent	Identify customer intent and route to the correct queue
After-Hours Support	Provide automated assistance when agents are unavailable

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Integration Points

Integration	Description
Architect Flows	Advanced routing or automation logic triggered by the assistant
Knowledge Base	Automated responses using knowledge articles — improves containment rate
Digital Channels	Chat, messaging (WhatsApp, SMS), and Web Messaging
Voice Channels	Voice bots for IVR interactions — speech recognition + NLU
Data Actions	API calls triggered by the assistant to retrieve or update external data

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Best Practices

Practice	Recommendation
Start with high-volume intents	Automate the most frequent customer requests first for maximum impact
Keep intents simple	Avoid overly complex intent structures that reduce NLU accuracy
Use knowledge articles	Well-written articles dramatically improve bot containment rate
Train with real customer data	Use actual customer utterances — not hypothetical ones
Monitor analytics continuously	Review bot performance, confidence scores, and fallback rates regularly
Provide easy escalation	Always ensure customers can reach a human agent quickly when needed

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Interview Cheat Sheet

Question	Answer
What technology do Assistants use?	Natural Language Understanding (NLU)
What is an Intent?	The goal or purpose of the customer's request
What are Utterances used for?	Training the NLU model with example customer phrases
What is an Entity?	A variable extracted from customer input (e.g., order number)
What happens when confidence is below the threshold?	The Fallback Intent fires — typically escalates to a human agent
What is Disambiguation?	Prompts the customer to clarify when multiple intents closely match