Alexa and Siri have become a part of our daily lives, these days. These AI agents literally take care of every personal routine like playing your favorite song, checking on the weather or recommending the best restaurant across the street.
What if you can have your own voice agent to manage the everyday tasks in your business?
- Taking care of that curious customer who wants to try out your product?
- Representing on behalf of a support agent who’s caught up in an important task or
- Become your customer’s favorite assistant for recommending what best suits them.
Think of having just one agent that can talk to millions of customers and do the work of a hundred human agents, without getting tired!
Doesn’t that sound like a ground-breaking upgrade for your business?
Well, if you are already convinced to build your own voice agent, stay with us for the next 5 mins. We’ll show you how to build one (surprisingly) within 30 minutes!
Who Is This Guide For?
Let’s make this clear, we’ve written this blog with the following people and roles in mind:
- Product Managers who are actively defining AI strategies for their teams.
- Tech Leads & Solution Architects designing system workflows to automate voice communications.
- AI/ML Engineers & Developers building and integrating speech interfaces for apps and web
- Business Leaders exploring automation across niches and focusing on elevating CX
- Tech Enthusiasts exploring AI Voice agent development
Overall, if you’re building a smart customer support assistant, automating repetitive tasks, or deploying AI in voice channels, this is for you.
What You’ll Learn
By the end of this guide, you can expect to understand:
What AI voice agents are, and how they actually work
The 6-stage workflow of a voice agent from audio input to spoken reply.
The 5-steps process to build your own AI Agent
What Is An AI Voice Agent?
An AI voice agent is a software that is built with capabilities to listen to what people say, figure out what they mean, and give a response in the most helpful way.
Remember, they are not everyday voice assistants like Siri or Alexa. These agents are built specifically for business purposes to get specific jobs done.
For example, when a customer initiates a voice inquiry, an AI voice agent will respond to them and perform necessary actions like appointment booking or coming up with a relevant answer from its knowledge base.
Do they do only that?
No.
After every conversation, they connect to company tools like customer databases (CRMs) and resource planning systems (ERPs), so they can pull up info and take action automatically.
This is a huge time saver, especially for strategic teams. Almost 70% of their work gets handled by an AI voicebot.
How exactly do they do it all? Let’s find out!
How Does An AI Voice Agent Work?
Like a human talking to another human, AI voice agents talk to humans in natural language, as well as talk to computers through codes.
There are several processes that happen behind the scenes, within the span a bot says “Hello” to a human.
Let’s check out how this works:
Assume you have implemented an AI voicebot for your team (Customer Support). This is what exactly happens between your customer - voice agent (AI) - support agent (human).
The customer enters your app, clicks on the record button, which mostly looks like this 🎙️
1. Voice Capture (Human Talk)
Now your phone or computer starts recording the voice. It cleans up the audio to remove background noise or echoes so the agent can hear better.
2. Speech-to-Text (Turns Speech into Words)
Any software will need this voice (analog) in the text format to understand the context.
So it uses speech recognition tools like Microsoft Azure Speech Service, MirrorFly Speech-to-text API, or Whisper by OpenAI to transcribe the voice data into machine readable text.
3. Understanding the Meaning (Figuring Out What You Want)
This is the point where AI Voicebots differ from regular software.
The agent will not only read the text, but will understand the meaning, emotion, tone and sentiment of the text using Natural Language Understanding (NLU) techniques powered by advanced machine learning models like transformers.
4. Text-to-Speech (Turns Response into Speech)
Once the system figures out what to say, it now starts to reply back into speech that sounds natural and human-like.
To perform this, providers like MirrorFly or Apphitect use Text-to-speech (TTS) engines integrated into their infrastructure.
5. Voice Output (It Talks Back)
Ultimately, your customer will now listen to the system’s voice reply through their app or computer, just like a normal conversation.
6. Smart Escalation
This is an optional stage. If the app user is happy with the answers and their inquiry is fulfilled, the conversation ends there.
If not, in cases they require further assistance from a human agent, the AI voice agent will provide a Click-to-call option to connect with a human support agent. Behind this CTC option are technologies such as SIP/ VoIP and WebRTC to initiate and route the calls internally.
This cycle keeps running so the voice agent can chat with your app users smoothly and naturally like you're talking to a real person.
So, this is how an AI voice agent works. Now, if you think it is a good idea to invest in building your own AI Voice Agent, here is a 5-step framework you need to follow.
5 Simple Steps To Build Your Own AI Voice Agent In 30 Minutes
A step-by-step guide for quickly creating a functional and reliable AI voice agent, even with minimal experience.
Step 1: Set Clear Goals
AI is everywhere these days and more than 68% of businesses have now started to adapt AI in one way or another into their business.
That does not mean, you need to rush into building complex AI systems just to keep up with the trend. Here’s what we recommend you to get started:
- Pick One Job: Do not spread out your goals. Not every part of your business needs an AI voice assistant or a chatbot. Start with one task for your voice agent, like rescheduling appointments or answering FAQs. Keep it as simple as possible to stay consistent and strong.
- Know Your Users: Think about who will use the agent and how on phones, in different languages, or older users. Design with user needs in mind.
- Start Small: Build a basic version (MVP) that solves one big problem. Rather than going big and getting stuck in the middle, you can simply build out a small agent, deploy it and then focus on upgrading it in the next sprint.
Step 2: Design a Clear Conversation Flow
Once your goals are clear or you are confident enough to get started, the next step is to start working on the conversation flow.
You’ll need to design the voice conversations, and train the models with knowledge bases to keep the chat between your agent and customers as smooth as possible.
Here are a few things you need to keep in mind while training the conversation flow.
1.Talk Like a Human: Use Natural Language Generation (NLG) and Neural Text-to-Speech (NTTS) Engines to train your agents with words that sound natural, short, simple, and friendly. Skip the jargon. People would not connect with the agent if the bot sounds too robotic.
2.Use ACP (Acknowledge, Confirm, Prompt):
- Acknowledge what the user said
- Confirm you understood
- Prompt what to do next
- This keeps things clear and smooth.
3.Plan for Mistakes: Sometimes the agent won’t understand. You need to have a backup of responses ready that guide the user or offer help from a real person.
4.Test for Real-Life Use: People have accents, get interrupted, or have noisy backgrounds. Make sure your agent can still handle the conversation well.
You can use Automatic Speech Recognition (ASR), Acoustic Echo Cancellation (AEC), Speaker Diarization and Context-Aware NLP/NLU Models to train your voice agents accordingly.
5.Guide the User: Use phrases like “Let’s start with your info” or “Almost done” to show progress and keep users comfortable.
Step 3: Choose the Right Technologies and SDKs
Each part of your voice agent has a job, and choosing the right tool for each part makes development easier and improves performance.
Using reliable, well-tested tools saves time and makes things work better for users right away.
Step 4: Build a Basic MVP or Add Pre-built SDK to Your App
This is the actual development part.
Here you’ll fall under one of the 2 categories:
- Building a full first version of your app
- Integrating an AI Agent SDK to your existing app
Be it any case, you can use a pre-built SDK like MirrorFly to build your voice agent. You can use the sample app and integrate the voice agent solution to get started. Or you can directly embed the agent into your app and customize it with your own brand logo, colors and elements.
In both cases, using MirrorFly AI Voice agent gives you total control over the data, security, customization, features, and infrastructure.
This is the stage where you can achieve complete AI agent development within 30 minutes.
All you need to do is:
- Build/ Buy your MVP
- Add MirrorFly AI Agent Solution
- Customize as per business requirement
- Go Live on your own servers or MirrorFly Cloud
This wraps the entire development process in half-an-hour!
Step 5: Test, Launch, and Track Performance
Roll out your voice agent in phases. Start with internal testing, then a small beta group, and finally go public.
Using the MirrorFly AI agent solution gives you the flexibility to choose where you’ll deploy your AI agent - on your own servers or on their cloud. Decide as per your requirements and launch the agent.
After launch, track key metrics like completion rate, escalation rate, CSAT scores, average handling time, time-to-first-word, agent accuracy, and sentiment to measure performance and user satisfaction.
Run critical tests before and after launch, including functionality, usability, performance, security, CRM integration, and voice input accuracy.
Keep monitoring the system continuously with tools like Inya.ai or Hamming AI to catch problems in real time and ensure a smooth, high-quality experience.
What’s Next?
Building an AI Voice Agent is no more a complex task, with reliable pre-built solutions available in the market. You can simply get the solution, add them to your existing system and start automating tasks with intelligent voicebots.
All you need to make sure is picking the right solution.
Make sure you the solution you pick ticks the below listed criteria:
- 100% customization
- Complete Data Control
- Full Source Code Access
- Custom Security
- On-premise/ On-cloud Deployment
- 1000+ Features
- 24/7 Support
- Compatibility with Modern Tech Stacks
- Uptime SLA
- Ultra-low Latency
- Minimum Average Response Time
- Dedicated Team for AI Agent Development
If the solution you choose fulfils all the above requirements, there’s no thinking back, go ahead and build amazing voice agents for your platform!
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