What Is A Conversational AI?
Conversational AI includes technologies of Natural Language Processing (NLP) & Machine Learning (ML), allowing systems to mimic natural human conversations. Yes! It understands, processes, and responds based on the context and sentiment.
It automates tasks involved in customer support, digital onboarding, lead qualification, payment reminders, and more. The chatbots, smart assistants, voicebots, IVRs, and NLP can be said as common interfaces of conversational AI. Curious to know how it works? Let's see.
How Does A Conversational AI Work?
The key components involve Natural Language Processing (NLP), Natural Language Understanding (NLU), Natural Language Generation (NLG), Machine Learning (ML), Deep Learning (DL), Large Language Models (LLM), Dialogue management, Speech Recognition, Text-to-Speech (TTS).
Let’s look them one by one.
1. Natural Language Processing (NLP)
NLP processes the spoken input, for example, the grammar, sentence structure, analyzes context, and intent to generate apt responses.
To ease the conversation, NLP works with below two:
NLU - Natural Language Understanding
NLG - Natural Language Generation
2. Natural Language Understanding (NLU)
The system analyzes the preprocessed input in order to find out the intent. NLU prepares specific information such as names, dates, or locations. This works out even for slang or idiomatic expressions. Here, the AI identifies what the user is trying to do.
NLU breaks text and speech into structured formats, so machines understand by analyzing grammar and sentiment. It's applicable in chatbots or voice assistants to extract meaning and make it a human-computer communication.
3. Natural Language Generation (NLG)
Natural Language Generation (NLG) is the AI that generates human-like responses that are context-aware plus adaptive. This is the output part of NLP, which includes NLU to interpret the user's input.
4. Machine Learning (ML)
Machine Learning (ML) allows systems to learn from data and interactions to understand human language, generate relevant responses. Moreover, it improves over time without direct programming. AI chatbot solutions are mostly backed by these ML algorithms.
Applications include:
Powers DL models to mimic human speech
Trains models for accurate response generation
NLP for intent understanding
5. Deep Learning (DL)
This is used along with Machine Learning. It fine-tunes accuracy and allows natural responses during complex or unpredictable scenarios. Deep learning handles open-ended questions. While ML models are suited for only basic queries & structured data analysis.
6. Large Language Models (LLM)
LLMs are integrated with deep learning, that leverage the capabilities of conversational AI to execute tasks for users. These tasks include fund transfer, create account, and more, all on customer’s behalf.
LLMs are trained on below deep learning architectures:
Transformer model
BERT, a Google's developed language model
Both improve the AI's context understanding. In fact, the virtual assistants deliver hyper-personalized experiences using LLMs.
7. Dialogue Management
It’s the next step that controls the flow and context of a conversation. This component tracks the conversation history, user intent to make sure AI provides a contextual reply. In simple words,
Dialogue Management = Decision Making Engine
8. Automatic Speech Recognition, Text-to-Speech
Automatic Speech Recognition converts spoken language to text. Text-to-Speech (TTS) will convert the AI-generated text into audio for the user.
ASR & TTS technology is applied in virtual assistants of Alexa, Google Assistant, and Siri, therefore creating a human-like conversation experience.
Conversational AI Functioning: Step-by-Step Process
Here is a step-by-step process of how conversational AI works. It makes the system understand, process & finally respond to the user's spoken language.
Step 1: User Input Collection
At first, a user provides input in the form of either text/voice to the system. It could be on an in-app messaging platform, website, or customer service phone hotline.
Step 2: Input Analysis
Here, the Speech-to-Text technology converts the audio into text. Then, Natural Language Processing (NLP) works to understand the user input. Following, Natural Language Understanding (NLU) confirms a deeper meaning by analyzing sentence structure and intention.
Step 3: Dialogue Management
Based on the context and past conversations, the system determines the next best action to provide relevant responses.
Step 4: Response Generation
Based on the understood intent, the AI’s Natural Language Generation creates a human-like response. Here, it depends on Machine Learning (ML), Deep Learning, and Large Language Models (LLMs) to produce more natural responses.
Step 5: Output Delivery
Finally, the text-to-speech technology converts the generated text response into voice.
Top 10 Conversational AI Solutions in 2025
Here’s the top 10 best conversational AI solution platforms list for 2025: MirrorFly, Apphitect, Twilio, ElevenLabs, Trinetix, Dialpad, Agora, Tavus, Yellow.AI and Kore.ai
1. MirrorFly
“Secure Conversational AI Assistant”
MirrorFly is an AI-powered CPaaS solution. Through its AI voice agent API developers can build intelligent chatbot & voicebot features. Highlight includes LLM-powered dialogues and intent-based automation.
Businesses choose this white-label AI agent for its unlimited customization and complete data control. Developers have the freedom to self-host this solution on their own servers or on MirrorFly Cloud.
MirrorFly’s conversational AI gathers and updates the details in CRM while the customer is talking. It doesn’t wait for the call to end, therefore you have real-time synchronization.
The voice agent is continuously trained on variety of datasets and inorder to improve the NLP accuracy, the feedback loops added. CRM system integration happens very easily and you can witness real-time responses.
Best for: Businesses looking for Custom Conversational AI Solution
Features:
- Natural Conversations with Advanced NLP & NLU
- Context-Aware Dialogues with Memory Retention
- LLM-Powered Dynamic & Natural Responses
- White Label Solution
- Full Data Ownership & Control
- Role-Based Access Control
- Built-in Conversation Summaries
- User Segmentation & Targeting
- Customizable Workflows
- Enterprise-Grade Security
- Intent Recognition & Entity Extraction
- Multi-Tenant Management Pricing: The SaaP product is available for a one-time license cost.
2. Apphitect
“Enterprise Conversational AI Software”
Apphitect is a self-hosted, white-label solution that helps create natural human-like conversations on your app. The platform offers APIs and SDKs with support for 100% customization and complete data ownership for businesses.
Your customer experience a personalized conversation when this solution is deployed across your web / app. Developers can choose flexible hosting on their own servers or the Apphitect Cloud.
Apphitect’s conversational AI supports multi-modal interactions across voice and text. Hence, a seamless natural experience delivered across all channels.
You don’t have to worry on data security. As the voice AI agent has strong data encryption and strict privacy protocols, with HIPAA and GDPR compliance.
Best for: Enterprise-level businesses looking for Secure On-Premise Voice Agent
Features:
- Canned Response Library
- Predictive Response Suggestions
- A/B Testing for Bot Responses
- Analysing Sentiments
- Automatic Language Detection
- AI combined Capability
- Instant transfer to Live Agents
Pricing:
Its one-time license can be purchased with a custom quote.
3. Twilio
“Best Conversational AI Agent”
Twilio's conversational AI can help deliver a personalized experience to your customers. The AI Assistant uses OpenAI's GPT-4 to connect with all your customer communication channels. Also, you can use your own LLMs.
Best for: businesses that need a flexible and open platform to build and host highly customizable AI agents.
Features:
- Voice Interactions with Ultra-Low Latency
- Customizable Prompts
- Flexible LLM Integration
- Omnichannel Support
- Agent Assist with Copilot
Pricing:
Twilio offers a pay-as-you-go pricing model
4. ElevenLabs
"Reliable Conversational AI Services"
ElevenLabs is a great fit for ultra-realistic voice synthesis, bringing emotion and natural flow to automated calls. They make content accessible globally. Automatic language detection helps in multilingual interactions.
**Best for: **brands that prioritize authentic-sounding conversations in voice.
Features:
- Custom voice & personalities
- Knowledge Base
- High-quality audio output
- Real-time voice cloning
- Multi-language support
Pricing:
- Popular package - $11 /mon (250 minutes)
- Business package - $1,320/mon (13,750 minutes)
- Enterprise package comes with custom pricing
5. Trinetix
"1 Conversational AI Solution"
Trinetix provides you with multimodal data processing and fine-tuned LLM agents. It solves complex business challenges across logistics and healthcare industries.
Best for: businesses looking to develop secure conversational AI solutions. You can achieve 5x better than chatbot quality.
Features:
- Chatbot to Live agent Transfers
- Multi Languague Capabilities
- Custom ML Models
- Analysing Sentiments
- End-to-End Support
Pricing:
Custom pricing provided based on your project's needs
6. Dialpad
"Trusted Conversational AI Voice Assistant"
Dialpad’s voice AI agent replicates human-like conversations and understands complex customer queries. Highlights are automatic personal info detection, custom data retention policies.
Best for: the contact center and sales team. Their AI engine trained on a billion minutes of anonymized business conversations.
Features:
- Real Time Call Transcription
- Automatic Post Call Summary
- Real-Time Agent Assist
- Very Easy No Code Setup
- Analysing Live Sentiment
Pricing:
- Standard plan at $15 per user/month
- Pro plan at $25 per user/month
- Enterprise plan available at custom pricing
7. Agora
"Leading Conversational AI Tool"
Agora's Conversational AI merges real-time audio with the leading LLMs. Over 60 billion minutes of live voice and video happen each month. It serves over 100 countries.
Best for: Customer support, education, gaming, and IoT industries that need a custom AI agent.
Features:
- Background noise suppress
- Intelligent interruption handling
- Reduced response delay
- Fully flexible model
- Very interactive AI avatars
Pricing:
Costs $0.0099/minute and extra $0.0166/minute added for ARES feature (Adaptive Recognition Engine for Speech)
8. Tavus
"Top-Rated conversational AI app"
Tavus produces conversational AI audio & video. It’s the first company to develop "human computing" by creating AI humans. Their APIs offer models for face rendering and speech with emotional intelligence.
Best for: organizations that need an AI agent that can see, hear plus respond to users just similar to humans, i.e, face to face manner
Features:
- Visual perception with empathy
- Multilingual Support
- Objectives + Guardrails
- Persona Builder
- Lifelike AI Replica
Pricing:
- Starter plan for $59/month
- Growth plan for $397/month
- The enterprise plan is available at a custom quote
9. Yellow.ai
"Powerful Conversational AI Software"
Yellow.ai is an agentic AI that automates enterprise service and manages customer & employee questions. DynamicNLP™ is its NLP system, pre-trained on billions of conversations across various industries.
Best for:
large, global enterprises with significant resources seeking to automate customer and employee support.
Features:
- Automate frontline support
- Conversational knowledge base
- Real-time sentiment analysis
- 100+ pre-built integrations
- Enterprise-grade security
Pricing:
The enterprise pricing plan can be tailored to your business needs.
10. Kore.ai
"Scalable Conversational AI Agent"
Kore.ai is an enterprise-grade platform for building and deploying AI-powered voice and chat assistants. It’s built on NLP & ML that understand user intent and therefore, provide natural responses.
Best for: Banking, healthcare, insurers, and telecom clients that require large-scale automation.
Features:
- Knowledge Graph (KG) Engine
- Pre-built Integrations
- Zero-Shot Intent Detection
- PII Detection and Protection
- Multilingual Support
Pricing:
Custom pricing provided based on the project's needs
Use Cases of Conversational AI
Conversational AI is changing many industries by enabling intelligent and human-like conversations. Here is the list of its use cases:
1. Voice Automation In Customer Service
Customer support voice agents are deployed across devices and messaging channels to automate queries. They instantly answer routine inquiries of customers and learn from interactions to handle complex questions.
2. Guide Shoppers In E-commerce
E-commerce conversational AI provides in-store assistance for shoppers from product search, order placement to checkout process. And with an AI chat API, businesses can integrate chatbots across e-commerce apps or websites.
3. Streamline Tasks In Enterprises
Employees use AI voice agents for self-service, such as resolving tickets, updating CRM records, tool access requests and generating invoices. Thus, enterprise conversational AI reduces the manual hand-offs.
4. Personalize Finance & Banking Journey
Customers can check balance, pay bills, transfer funds, and apply for credit cards, all using the finance & banking conversational AI agents.
5. Simplify Tasks In Call Centers
Conversational IVR can recognize user intention with sentiment in real time. Here, the AI agent transcribes and pulls relevant data for the customer query. It guides the human agent in the call center to answer faster.
6. In-Game Assistance For Players
The AI agent uses natural language processing to understand player requests. It answers about game mechanics, adjusts in-game settings, and more. Thereby, reducing gamers’ frustration.
7. Answer Property Inquiries In Real Estate
It automates tasks: answering buyer-seller property inquiries, providing custom property suggestions, or scheduling visits.
8. Enhance Guest Experiences In Hospitality
In the hospitality and travel industries, the voice AI agent assists in booking & providing travel information. It can also help in reschedule or cancel bookings.
9. Appointment Booking In Healthcare
Healthcare conversational AI automates appointment scheduling, checks practitioner availability, answers medical queries, and more.
10. Streamline Tasks In HR & Employee Support
During employee onboarding, the voice agents streamline the process by providing information & guiding new employees with tasks. The conversation covers company policies, orientation sessions & FAQs.
What Are The Benefits of Using Conversational AI?
Here, listed below are the breakdown of Conversational AI’s key benefits.
- Enterprise-grade Scalability For High-Volume Calls Conversational AI is designed for scalability, enabling businesses to handle millions of calls at once. At the same time, it doesn’t compromise quality or significant increase in cost.
- Reliable With 99.99% Uptime AI voice agents do not need breaks or operate within fixed business hours. This ensures the business is always accessible to its customers for customer support.
- Multilingual Support Conversational AI supports multiple languages. Deploying language-specific models enhances understanding and response accuracy in multilingual environments.
- Region-specific Compliances Without powerful data encryption, businesses risk non-compliance with regional regulations. But conversational AI safeguards them by adhering to HIPAA and GDPR standards.
- 24/7 Automation The conversational AI is available 24/7. All communication channels are available to users constantly. Thus, customers get instant answers whenever they need.
- Respond Under 500ms This AI agent solution delivers responses faster. This ensures potential customers remain active and resolves their issues quickly.
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