Glossary
AI Glossary for Customer
Communication Automation
Understand the key terms behind modern AI-powered customer communication.
AI Glossary
for Customer
Communication
Automation
Understand the key terms behind modern AI-powered customer communication.
AI Automation Is More Than a Chatbot
Customer communication is changing fast, and AI has moved well past simple scripted chatbots and basic phone menus.
Today’s AI agents understand customer intent, respond in natural language, work across text and voice, connect to company systems, support human agents, and turn conversations into measurable business outcomes.
This glossary groups the terms that matter most by topic, so you can quickly see how the different technologies fit together in real enterprise use cases.
AI Automation
Is More Than
a Chatbot
An enterprise AI chatbot is an intelligent conversational assistant designed to communicate naturally with website visitors, customers and employees across chat, webchat and digital channels.
It combines real-time conversations, automation and business system integrations to answer questions, qualify leads, support users and guide them through key processes directly on your website.
Core AI Concepts
Conversational AI
Conversational AI lets machines communicate naturally with people through text or voice answering questions, guiding users, automating requests, routing conversations, and triggering actions in business systems.
AI Agent
An AI agent understands a request, evaluates context, decides what to do next, and takes action. Unlike a simple chatbot, it can connect to tools, pull data, update systems, or escalate to a human.
Conversational AI Agent
A conversational AI agent is built specifically for communicating with customers or employees, whether through webchat, voice, email, apps, portals, or digital human interfaces.
AI Workforce
An AI workforce is a group of AI agents deployed across an organization, each handling a specific role answering website questions, processing emails, calling customers, or analyzing conversations.
Enterprise AI
Enterprise AI is built for real business operations, which means it has to meet the bar for security, scalability, reliability, governance, integrations, monitoring, and compliance.
AI Customer Support
AI customer support applies artificial intelligence to improve or automate customer service from chatbots and voicebots to mailbots, agent copilots, self-service, routing, summaries, and analytics.
Digital Self-Service
Digital self-service lets customers resolve a request without waiting for a human agent checking a status, updating details, booking an appointment, submitting a request, or getting product support.
AI-First Customer Service
With AI-first customer service, AI handles the first layer of customer interaction, automating routine and repetitive requests while escalating complex or sensitive cases to human specialists.
Hybrid Workforce Model
A hybrid workforce model pairs AI agents with human teams: AI handles repetitive, scalable tasks, while people focus on complex decisions, empathy, negotiation, and exceptions.
Want to See How AI Agents Work in Practice?
Want to See How
AI Agents Work
in Practice?
Born Digital helps companies automate customer communication across voice, chat, email, analytics, and digital human experiences.
AI Communication Channels
Website Chatbot
A website chatbot is an AI assistant embedded on a website that helps visitors find information, understand products, qualify as leads, and move toward the next step like submitting a form or booking a demo.
Webchat
Webchat is a real-time messaging channel on a website or in an app, handled by AI, a human agent, or both. Modern webchat can carry a customer through a complete journey, not just a simple Q&A.
Chatbot
A chatbot holds text-based conversations with users. Modern AI chatbots draw on language models, knowledge bases, and integrations to handle more complex questions and give more useful answers.
Voice AI
Voice AI lets machines understand spoken language, respond with natural-sounding speech, and act in real time used in customer service lines, outbound calls, reminders, reservations, surveys, and lead qualification.
Voicebot
A voicebot is an AI system that speaks with customers by phone or another audio channel: it recognizes speech, understands intent, responds by voice, and can connect to company systems.
Inbound Voicebot
An inbound voicebot handles incoming calls answering questions, verifying information, checking request status, rescheduling appointments, collecting details, and routing calls to the right team.
Outbound Voice AI
Outbound voice AI proactively calls customers, leads, or employees, and is well suited to appointment confirmations, payment reminders, feedback collection, lead qualification, onboarding, and service notifications.
AI Mailbot
An AI mailbot automates incoming email handling: classifying messages, detecting intent, assigning priority, suggesting replies, routing emails, and triggering workflows in connected systems.
Digital Human
A digital human is an AI assistant with a visual, voice, or avatar-based interface, combining conversational AI, voice AI, automation, knowledge, and integrations into a more human-like digital experience.
AI Avatar
An AI avatar is the visual or voice representation of an AI assistant. The avatar is just the interface its real value comes from the intelligence, knowledge, and processes running behind it.
Voice Concierge
A voice concierge is a personalized voice AI assistant built for more complex or premium customer scenarios, helping with recommendations, bookings, service navigation, and high-touch support.
Omnichannel Customer Experience
An omnichannel customer experience lets customers move between channels without losing context a conversation might start on a website, continue in chat, and finish by phone, with history and intent preserved throughout.
Multimodal Customer Experience
A multimodal customer experience blends several ways of interacting into one journey: a customer might speak, type, click, upload a document, fill out a form, confirm an option, or talk to a digital avatar.
How AI Understands
Language and Speech
How AI
Understands
Language
and Speech
Large Language Model
A Large Language Model, or LLM, is an AI model trained on large volumes of text. It can generate responses, summarize information, recognize meaning, draft content, and help AI agents communicate naturally.
Generative AI
Generative AI creates new content. Text, speech, images, summaries, or code. In customer communication, it’s used to generate replies, summarize calls, draft emails, and personalize responses.
Natural Language Processing
Natural Language Processing, or NLP, is the field of AI focused on processing human language, helping machines analyze text and speech, identify topics, and understand communication patterns.
Natural Language Understanding
Natural Language Understanding, or NLU, focuses on what the user actually means helping AI grasp intent, context, urgency, and the purpose behind a customer request.
Natural Language Generation
Natural Language Generation, or NLG, lets AI produce natural text or spoken responses, used for customer replies, email drafts, summaries, and guided next steps.
Automated Speech Recognition
Automated Speech Recognition, or ASR, converts spoken language into text. It’s essential for voicebots and voice AI agents, since it’s what lets a system understand what a caller is saying.
Continuous ASR
Continuous ASR recognizes speech in real time as the customer speaks, making voice interactions faster and more natural because the system never has to wait for a manual cue.
Speech Synthesis
Speech synthesis, also known as Text-to-Speech or TTS, converts written text into spoken audio. Modern TTS produces natural-sounding voices with distinct tones, pacing, and expression.
Barge-In
Barge-in lets a caller interrupt a voice AI agent mid-sentence: the system stops talking, starts listening, and responds to the new input a small feature that’s critical for natural phone conversations.
Language Detection
Language detection identifies the language a customer is using, so AI agents can switch languages automatically or route the conversation to the right language version.
Sentiment Analysis
Sentiment analysis reads the emotional tone of a conversation, picking up on whether a customer sounds satisfied, frustrated, confused, neutral, or urgent.
Speaker Recognition
Speaker recognition identifies or verifies a person from their voice. It can support biometric authentication, provided it meets the organization’s security, privacy, and legal requirements.
Multimodal Customer Experience
A multimodal customer experience blends several ways of interacting into one journey: a customer might speak, type, click, upload a document, fill out a form, confirm an option, or talk to a digital avatar.
Automate Voice, Chat, and Email
Without Losing Control
Automate Voice,
Chat, and Email
Without
Losing Control
Born Digital AI agents can support customers across channels while staying connected to your systems, knowledge, and business rules.
Knowledge, Data,
and Enterprise Integrations
Knowledge, Data,
and Enterprise
Integrations
Retrieval-Augmented Generation
Retrieval-Augmented Generation, or RAG, lets AI answer from a specific knowledge base instead of relying only on general model knowledge improving accuracy, consistency, and relevance.
Knowledge Base
A knowledge base is the structured or unstructured information an AI agent draws on: FAQs, product documentation, internal manuals, policies, process instructions, or technical documents.
Knowledge-Driven AI
Knowledge-driven AI generates answers from verified company knowledge, making it useful for customer support, internal helpdesks, technical documentation, sales assistance, and recurring questions.
Context Window
The context window is how much information a language model can process at once — instructions, conversation history, retrieved knowledge, and business context, all combined.
Agent Memory
Agent memory lets an AI agent carry information across a conversation or across multiple interactions. Short-term memory supports the current dialogue; long-term memory enables more personalized service.
Prompt Engineering
Prompt engineering is the design and optimization of instructions given to a language model defining tone, behavior, rules, data sources, limits, and response style.
Tool
A tool is any external capability an AI agent can call on: an API, CRM, database, calendar, ticketing system, payment gateway, knowledge base, or internal application.
Model Context Protocol
Model Context Protocol, or MCP, is a standard for connecting AI agents to external tools, data sources, and services, helping AI systems safely discover and use whatever capabilities are available.
Enterprise Integrations
Enterprise integrations connect AI agents to business systems CRM, ERP, ticketing platforms, telephony, customer portals, databases, knowledge bases, and workflow tools.
Workflow Automation
Workflow automation completes process steps without manual input. An AI agent can collect information, verify data, create a request, send a confirmation, and update a CRM record — all in sequence.
Robotic Process Automation
Robotic Process Automation, or RPA, automates repetitive digital tasks such as copying data, filling in forms, reading screens, or moving information between systems.
Hyperautomation
Hyperautomation combines several technologies — AI, machine learning, RPA, NLP, analytics, and workflow automation with the goal of automating entire processes, not just isolated tasks.
AI Agent Management
and Advanced Automation
AI Agent
Management
and Advanced
Automation
Agentic AI
Agentic AI describes systems that can plan and execute multi-step tasks. Rather than answering a single question, the agent evaluates context, selects a process, uses tools, and works toward a defined goal.
Agentic Workflow
An agentic workflow is a dynamic process managed by one or more AI agents, where the path can change based on customer input, available data, business rules, and real-time context.
Agentic RAG
Agentic RAG adds decision-making to knowledge retrieval: the agent decides what information it needs, where to search, how to compare results, and when to ask for more context.
Agent Orchestration
Agent orchestration coordinates the work of multiple AI agents deciding which agent handles a task, how context passes between them, which tools get used, and when to bring in a human.
Multi-Agent System
A multi-agent system puts several specialized AI agents to work together: one may talk to the customer, another searches for data, another performs an action, and another checks quality.
Agent Handover
Agent handover transfers a conversation from AI to a human agent, typically because a case is too complex, too sensitive, outside the AI’s scope, or the customer has asked for a person.
Agent Copilot
An agent copilot supports human agents during live interactions, suggesting answers, summarizing history, retrieving information, flagging risks, and cutting down after-call work.
Next Best Action
Next best action is an AI-generated recommendation for the most useful next step a follow-up question, an offer, an escalation, a retention action, or a process step.
Intent-Based Routing
Intent-based routing directs customers based on what they actually need: AI identifies the intent and sends the request to the right AI flow, team, queue, or human specialist.
Skill-Based Routing
Skill-based routing sends a request to whichever human or AI agent is best suited to handle it, based on capability rather than simple availability.
Predictive Routing
Predictive routing uses historical data and machine learning to estimate which agent, team, or workflow is most likely to produce the best outcome.
Interactive Voice Response
Interactive Voice Response, or IVR, is a phone system that interacts with callers through voice prompts and keypad selections the traditional “press 1 for…” menu.
Conversational IVR
Conversational IVR replaces traditional phone menus with natural speech, so customers can simply say what they need instead of working through long menu options.
Natural Language IVR
Natural Language IVR understands freely spoken requests, multiple intents, context, and industry-specific vocabulary, making voice self-service noticeably more natural and efficient.
Automatic Call Distributor
An Automatic Call Distributor, or ACD, routes incoming calls to agents, queues, teams, or automated systems according to predefined rules.
From AI Concepts
to Real Business Automation
From AI Concepts
to Real Business
Automation
Born Digital designs and implements AI agents that do more than answer questions. They automate tasks, support teams, and improve customer experience.
Analytics, Measurement,
and Optimization
Analytics,
Measurement,
and Optimization
Conversational Analytics
Conversational analytics analyzes customer calls, chats, emails, and other interactions to surface recurring issues, automation opportunities, sentiment trends, compliance gaps, and operational patterns.
AI Observability
AI observability monitors how AI agents behave in production, helping teams understand why an agent responded the way it did, what knowledge it drew on, and where it needs improvement.
Automation Discovery
Automation discovery identifies which customer requests are the strongest candidates for automation, by analyzing historical conversations, calls, emails, tickets, and operational data.
AI Agent Evaluation
AI agent evaluation measures the quality, safety, accuracy, and business impact of an AI agent, both before launch and throughout production.
Containment Rate
Containment rate is the percentage of interactions resolved by AI without a human handover a key metric for chatbots, voicebots, and self-service automation.
Average Handle Time
Average Handle Time, or AHT, is the average time it takes to handle a customer interaction, including talk time, waiting time, and follow-up administration.
First Contact Resolution
First Contact Resolution, or FCR, measures how many customer requests get resolved on the first contact. Higher FCR usually means a better customer experience and less operational load.
Customer Effort Score
Customer Effort Score, or CES, measures how much effort a customer had to put in to resolve a request lower effort generally means a better experience.
Net Promoter Score
Net Promoter Score, or NPS, measures customer loyalty by asking how likely customers are to recommend a company, product, or service.
Digital Wait Treatment
Digital wait treatment uses AI to make waiting time useful collecting information, verifying identity, offering self-service, or preparing context for a human agent.
Multivariate Testing in AI
Multivariate testing compares multiple AI agent configurations at once, letting teams test prompts, knowledge bases, routing, guardrails, escalation rules, and tone of voice side by side.
Security, Governance,
and Quality Control
Security,
Governance,
and Quality
Control
AI Governance
AI governance defines how AI is used, monitored, approved, and controlled within an organization, covering security, compliance, policies, auditability, and accountability.
AI Guardrails
AI guardrails are the rules and restrictions that keep AI behavior within safe boundaries, helping prevent inaccurate, inappropriate, non-compliant, or off-brand responses.
AI Hallucination
AI hallucination happens when AI produces an answer that sounds confident but is inaccurate or unsupported by available data. Knowledge bases, guardrails, testing, and monitoring all help reduce the risk.
GDPR
GDPR is the European regulation for personal data protection. It matters a great deal when AI systems process voice recordings, transcripts, customer history, identification data, or analytics.
Enterprise-Grade AI
Enterprise-grade AI is ready for real business use: secure, scalable, reliable, monitored, integrated, and governed according to company rules.
Composite AI
Composite AI combines several methods, language models, rules, RAG, predictive analytics, workflow automation, and deterministic logic to make AI systems more reliable and controllable.
Machine Learning
Machine learning lets systems learn from patterns in data, and underpins classification, prediction, sentiment analysis, routing, and optimization.
Deep Learning
Deep learning is a type of machine learning built on multi-layer neural networks. It powers much of today’s speech recognition, language processing, generation, and image analysis.
Voice, Cloud, and Contact
Center Infrastructure
Voice, Cloud,
and Contact
Center
Infrastructure
Cloud-Native Architecture
Cloud-native architecture is an approach to building applications for cloud environments, typically using microservices, containers, automated deployment, scaling, and high availability.
CCaaS
Contact Center as a Service, or CCaaS, is a cloud-based contact center model that replaces part of the traditional infrastructure with a flexible, cloud-delivered service.
Contact Center
A contact center is the operational and technology hub for customer communication, spanning phone, chat, email, messaging, social media, self-service, and other channels.
Contact Center Agent
A contact center agent is a person who handles customer interactions. In modern operations, agents typically work alongside AI copilots, summaries, recommendations, and automation tools.
Contact Center AI
Contact Center AI applies artificial intelligence to contact center operations, covering call automation, chat automation, agent assistance, routing, analytics, summaries, and process automation.
Auto Dialer
An auto dialer automatically dials phone numbers, connecting calls to human agents, playing recorded messages, or working alongside AI voice agents.
SIP Protocol
Session Initiation Protocol, or SIP, is a standard for starting, managing, and ending voice or video communication over IP networks.
SIP Trunk
A SIP trunk is a virtual phone line connecting a company’s phone system to the public telephone network or a VoIP provider.
Session Border Controller
A Session Border Controller, or SBC, protects, controls, and routes voice communication at the edge of a telephony network.
Voice Gateway
A voice gateway connects conversational AI systems to telephony networks, enabling AI agents to take part in real phone calls.
PSTN
The Public Switched Telephone Network, or PSTN, is the traditional public telephone network that connects calls between phone numbers.
RTP
Real-time Transport Protocol, or RTP, carries audio and video data during live communication.
WebRTC
WebRTC enables real-time voice, video, and data communication directly in a browser, with no extra software required.
SSML
Speech Synthesis Markup Language, or SSML, controls how synthetic speech sounds defining pauses, pronunciation, emphasis, speed, and reading style.
TTS Caching
TTS caching stores frequently used voice outputs in advance, reducing latency for repeated phrases like greetings, confirmations, and standard instructions.
Low-Code Platform
A low-code platform lets teams build applications and automation with minimal manual programming in AI projects, this speeds up prototyping, testing, and workflow design.
Build AI agents like
building blocks
Build AI
agents likebuilding blocks
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Our modular platform lets you build AI agents up to 10× faster than traditional development. Put together what you need, update anytime, and scale as you wish — all without writing a single line of code.
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