Ever tried calling a big company and got stuck in a “phone tree”? You know, where a robot voice tells you to “Press 1 for Sales” or “Press 2 for Support,” but none of the options actually fit your problem? It’s super annoying.
Most companies still use those old systems, but things are changing fast because of AI. Instead of pushing buttons, you can just talk like a normal person, and the AI figures out what you need. This is called AI-driven voice routing.
In this post, I’m going to show you how to design these new call flows. We’ll talk about how to help the AI understand what a caller wants and how to make sure the “robot” doesn’t get confused. It’s basically like building a smart map for phone calls. Let us dive in.
Core Components: The “Modern Voice Stack”
1. STT (Speech-to-Text): The “Ears”
First, the AI needs to hear what the person is saying. The STT takes the sound of the human voice and turns it into written words.
- Why it matters: If the “ears” are bad, the AI will get the words wrong. You need fast tools like Deepgram or AssemblyAI so there isn’t a long silence while the AI “listens.”
2. LLM/NLU (The Brain): The “Thinker”
Once the voice is turned into text, the LLM (Large Language Model) reads it to figure out the intent. Intent is just a fancy word for “what the person actually wants.”
- Example: If a caller says, “My package never showed up,” the brain figures out the intent is Shipping Issue. Common “brains” are OpenAI, Anthropic, or Dialogflow.
3. TTS (Text-to-Speech): The “Voice”
After the brain decides what to say back, it needs to speak. The TTS takes the written response and turns it back into a voice.
- The Goal: You want it to sound like a real person, not a glitchy computer. Companies like ElevenLabs or Cartesia make voices that sound very human.
4. Orchestration: The “Glue”
This is the part that connects everything. It hooks the phone line (like IDT Express, Twilio) to the ears, the brain, and the voice.
- How it works: Without the glue, the parts can’t talk to each other. Tools like Vapi or Retell act as the manager to make sure the data moves fast from one step to the next.
- Finding a reliable telco partner who understands the telco infrastructure for Voice AI services is key.
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Step-by-Step Design Framework
Now that we have all the parts, we need to build the “map” that tells the AI where to send people. You don’t want your callers getting lost! Here is how you build it, step-by-step.
1. Figure Out the “Big Reasons”
Before you build anything, look at why people call. Most people call for about five main things (like “Where is my order?” or “I need to change my password”).
- The Goal: Make sure the AI is really good at these five things first. These are your Happy Paths.
2. The Greeting
Don’t just say “How can I help you?” That is too broad. It’s better to give the caller a hint.
- Try this: “Hi! I can help you with tracking orders, billing, or technical support. What can I do for you today?” This helps the caller know what to say.
3. Making the Decision (Routing)
When the caller speaks, the AI “Brain” looks at their words.
- Hard Rules: If someone screams “EMERGENCY,” the AI should instantly send them to a human. No questions asked.
- Smart Decisions: If the caller says, “I can’t log in,” the AI sends them to the Tech Support path.
4. Using What You Already Know
A smart system checks the caller’s phone number against your database.
- Example: If a “VIP” customer calls, the AI can see that and say, “Hi Alex! I see you have a pro account. Let me get you to a specialist right away.”
5. The “Safety Net”
Sometimes the AI gets confused. Maybe the caller has a thick accent or is in a noisy place.
- The 2-Strike Rule: If the AI doesn’t understand the caller two times in a row, it should say, “I’m sorry, I’m having trouble. Let me get a human to help you.” This keeps the customer from getting angry.
Best Practices for Voice UX
1. Keep it Short In a blog or an email, long sentences are fine. On a phone call, they are terrible. If the AI talks for 30 seconds straight, the caller will forget how the sentence started.
- The Rule: Keep AI responses under 15 seconds. If the answer is long, break it into small chunks.
2. Handling “Barge-in” Have you ever tried to interrupt someone because you already knew what they were going to say? That is called Barge-in.
- The Fix: Your AI needs to “listen” even while its “mouth” is moving. If the caller says “Stop” or “I already know that,” the AI should stop talking immediately and listen.
3. Speed is Everything (Latency) If you ask a friend a question and they wait three seconds to answer, you’d think they fell asleep. That wait time is called latency.
- The Goal: Try to get the AI to respond in less than 1 second. Using “streaming” STT (where the AI starts “reading” while the person is still talking) helps make this happen.
Transitioning: The “Warm Handoff”
Eventually, the AI might need to give the call to a real person. This is the most important part to get right.
Don’t Make Them Repeat Themselves The worst thing is when a human picks up and asks, “How can I help you?” after you just explained everything to the AI for five minutes.
- The Solution: The AI should send a “Summary Note” to the human’s computer screen.
- What’s in the note: * Who is calling?
- What are they upset about?
- What did the AI already try to do?
The “Transition” Message The AI should be polite. Instead of just a click and hold music, it should say: “I’m going to get a human expert to help you with your billing. I’m sending them our notes now so they’re ready for you. Please hold for one moment.”
Measuring Success (KPIs)
Once your AI voice system is running, you need to make sure it’s actually doing a good job. You can’t just “set it and forget it.” You have to look at the numbers to see if your callers are happy or if they are hanging up in a huff.
The first big thing to look at is the Containment Rate. This is basically a way of asking, “Did the AI finish the job?” If 100 people call and the AI solves the problems for 80 of them without needing a human, you have an 80% containment rate. High numbers here usually mean your “Brain” is smart enough to handle the work. But be careful! You also have to check if people are hanging up because they got mad. That’s why you look at the Sentiment Score. This is where the AI reads the transcript to see if the caller sounded happy, confused, or angry by the end of the call.
Another important number is Routing Accuracy. This tracks if the AI sent the caller to the right place. If someone wanted “Billing” but the AI sent them to “Tech Support,” that is a fail. It’s like a GPS giving you the wrong directions. You also want to track the Average Handle Time. Since the AI can look up data way faster than a person can, it should be able to finish calls much quicker than a human agent. If the calls are taking forever, your AI might be talking too much or asking too many questions.
By watching these numbers every week, you can see where the “map” is broken and fix it so the calls get smoother and smoother over time.
Building a smart voice routing system is a lot like teaching a new employee how to handle the phones. It takes some time to get the “Brain” and the “Ears” working perfectly, but once you do, it changes everything. Moving away from old-school menus to real AI conversations makes life much easier for your customers because they can finally just say what they need and get an answer fast. Even though the technology behind it is pretty complex, the goal is simple: make the phone call feel as natural as talking to a friend while making sure nobody gets lost in the system.
If you are ready to start building your own AI call flows, you need a solid foundation to carry those voices. IDT Express provides the high-quality voice routes you need to make sure your AI sounds crystal clear and never drops a call. We specialize in supporting voice AI technology, giving you the global reach and reliability required to connect your “AI Brain” to callers all over the world. Using a partner like IDT Express ensures that your technical “Glue” is strong enough to handle as many calls as your business can grow.
IDT has been a leader in telecom solutions since 1990, listed on NYSE, headquartered in Newark, New Jersey. Approx $1.5B market cap, with billions of minutes terminated annually.
