Deploy a Conversational AI Voice Assistant with Control

The era of the simple, reactive chatbot is over. Today, the goal is to build and deploy a Conversational AI Voice Assistant that is not just intelligent but also fully controllable. This means creating an agent that can do more than just answer questions; it can execute complex workflows, switch context, escalate to humans, and be monitored and tuned in real time. For businesses, this level of control is non-negotiable. It’s the key to ensuring security, compliance, and a truly reliable customer experience.

With a rich ecosystem of no-code platforms and pro-code frameworks, developers now have unprecedented control over their AI’s logic. However, a critical and often overlooked challenge emerges at the point of deployment. A brilliant, highly controlled AI is useless if it can’t be deployed on the channels your customers use most. For high-stakes interactions, that channel is almost always the telephone, and this is where most projects lose control entirely.

What is a Controlled Conversational AI Voice Assistant?

A controlled Conversational AI Voice Assistant is a system that combines real-time voice interaction with a sophisticated layer of user- and system-defined controls. It’s an evolution of the standard voicebot, built on a foundation of several key technologies:

• Speech-to-Text (STT) and Text-to-Speech (TTS): The “ears and mouth” that enable natural, spoken dialogue.
• Natural Language Understanding (NLU): The AI “brain” that deciphers user intent.
• Custom Control Logic: The “nervous system.” This is the set of rules, workflows, and API integrations that allow the assistant to perform specific actions, such as routing a call, updating a CRM, or pausing a task to retrieve data.
• Monitoring and Analytics: The “eyes.” Dashboards and logs that provide real-time visibility into the assistant’s behavior, allowing teams to observe, intervene, and optimize its performance.

This combination creates a powerful, enterprise-grade agent that can be managed and tuned by both business and technical users.

The Deployment Trap: Where Conversational Control Meets a Brick Wall

You have successfully built this system. Using a platform like Voiceflow or Rasa, you have designed intricate conversational flows, integrated your backend business logic, and created a Conversational AI Voice Assistant with an impressive level of control. It works perfectly in your development environment. Now, it’s time to deploy it on your company’s support hotline. This is where you hit the deployment trap.

The very platforms that give you granular control over your AI’s conversational logic have no native ability to give you control over a live phone call. The Public Switched Telephone Network (PSTN) is a completely different universe from the web, with its own complex protocols and infrastructure requirements.

To connect your bot to a phone number, you would need to build a highly specialized telephony stack from scratch. This would force your team to solve a host of challenging problems:

• Managing SIP (Session Initiation Protocol) trunks to connect to telecom carriers.
• Building and maintaining real-time media servers to handle raw audio streams.
• Architecting a system to programmatically manage call control actions like transfers, holds, and terminations for thousands of concurrent sessions.

Your team, expert in AI and conversation design, is suddenly forced to become telecom engineers. The fine-grained control you worked so hard to build into your AI’s brain cannot be executed in the real world because you have no control over the phone line itself.

FreJun: The API for True Call Control

This is the exact problem FreJun was built to solve. We are not another AI platform. We are the specialized voice infrastructure layer that provides the API for true, programmatic call control. FreJun connects the sophisticated, controlled Conversational AI Voice Assistant you’ve already built to the global telephone network.

We handle all the complexities of telephony, so you can focus on making your AI smarter.

• We are AI-Agnostic: You bring your own AI “brain.” FreJun integrates seamlessly with any backend, whether it’s built on Voiceflow, Rasa, or a custom stack of APIs.
• We Provide Call Control Primitives: Our developer-first API gives your backend the power to execute real-world call actions. When your AI’s logic decides to escalate, your backend can use FreJun’s API to transfer the call instantly.
• We Guarantee Reliability and Scale: Our globally distributed, enterprise-grade infrastructure ensures your phone line is always online and ready to handle high call volumes with the same level of control and precision.

FreJun provides the missing link, the API that allows your AI’s logical decisions to be translated into real-world actions on a live phone call.

Pro Tip: Design Your AI’s Logic with Call Actions in Mind

When designing your conversational flows, think of your AI’s outputs not just as text responses but as commands for your voice infrastructure. For example, instead of just generating the text “I’m transferring you to a specialist,” your AI’s logic should trigger a specific function in your backend that makes an API call to FreJun.transfer(). This approach creates a clean separation of concerns and a highly extensible system.

The Two Layers of Control: A Strategic Comparison

Layer	Conversational Control (The AI’s Brain)	Call Control (The Infrastructure Layer – Provided by FreJun)
What it Controls	The flow of the dialogue, user intent, context, and responses.	The state of the live phone call itself: answering, streaming audio, transferring, holding, and terminating.
Example Platforms/Tools	Voiceflow, Rasa, Google Dialogflow, OpenAI, Custom LLM frameworks.	FreJun’s Voice API and SDKs.
Key Features	Intent recognition, dialogue management, context switching, API integrations for data.	Programmatic call transfer, call hold with music, real-time audio streaming, call recording control.
The Developer’s Role	Designing the conversational experience and AI logic.	Executing real-world call actions based on the AI’s decisions.

How to Deploy Your Conversational AI Voice Assistant with Control? (Step-by-Step)

This guide outlines the modern architecture for deploying a controlled voice assistant that can handle real phone calls.

Step 1: Build Your Controlled AI “Brain”

First, use your chosen platform (like Voiceflow or Rasa) to design the core conversational logic. This is where you define your use cases, design your interaction flows, and program the control logic, such as the triggers for escalating a call to a human.

Step 2: Provision Your Telephony Channel with FreJun

Instead of building a telecom stack, simply sign up for FreJun and instantly provision a virtual phone number. This number is now the direct line to your AI assistant.

Step 3: Connect Your Brain to the FreJun API via Your Backend

In the FreJun dashboard, configure your new number’s webhook to point to your backend server’s WebSocket endpoint. Your backend will act as the intermediary between FreJun’s infrastructure and your AI’s logic.

Step 4: Orchestrate the Real-Time Conversational Flow

When a customer dials your FreJun number, our platform establishes a real-time audio stream to your backend. Your code will then:

1. Receive the raw audio stream and a unique session ID from FreJun.
2. Pipe this audio to your STT API to be transcribed.
3. Send the transcribed text to your AI “brain” for processing.

Step 5: Execute Control Actions with FreJun’s API

This is where the two layers of control meet. Your AI “brain” will generate a response that includes both text for the user and a potential control action.

• If the AI just wants to respond, your backend sends the text to your TTS API and streams the synthesized audio back to FreJun.
• If the AI’s logic determines a transfer is needed, it will return a command like {“action”: “transfer”, “target”: “sales_queue”}. Your backend then makes a corresponding API call to FreJun to execute the transfer.

This architecture gives you a powerful, decoupled system where your AI focuses on what to do, and FreJun handles how to do it on the phone.

Key Takeaway

A truly controlled Conversational AI Voice Assistant requires two distinct layers of control. The first is conversational control, which you build into your AI’s logic using platforms like Voiceflow or Rasa. The second, much harder layer is call control, which is the ability to programmatically manage a live phone call. FreJun provides this second layer as a simple, powerful API, allowing you to deploy a complete, enterprise-grade solution without the immense cost and complexity of building your own telecom stack.

Best Practices for a Flawless and Secure Deployment

• Balance Automation and Human Oversight: Design clear escalation paths and control checkpoints in your AI’s logic for complex or ambiguous scenarios.
• Prioritize Security and Compliance: Handle all voice data and logs with strict security measures. Ensure both your application and your infrastructure partner comply with regulations like GDPR.
• Continuously Monitor and Optimize: Use analytics from both your AI platform and your voice infrastructure to get a complete picture of your assistant’s performance. Track latency, intent accuracy, and call transfer success rates to continuously improve the user experience.
• Keep Knowledge Bases Well-Structured: The reliability of your assistant’s control actions depends on the accuracy of its decisions. Maintain a clear and concise knowledge base to ensure your AI has the right information.

Final Thoughts: From a Controlled Bot to a Powerful Business Tool

You’ve invested in building a sophisticated Conversational AI Voice Assistant with an impressive level of control over its logic. You’ve taught it to be smart, secure, and helpful. Now, it’s time to put it to work in the real world.

Don’t let your brilliant creation be limited by the confines of a digital channel. The strategic path forward is to combine your powerful AI with an equally powerful voice infrastructure. By leveraging a specialized platform like FreJun, you can bridge the deployment gap and give your bot the ability to execute its commands on the world’s most ubiquitous communication network. You transform it from a clever piece of software into a powerful, controllable business tool that can serve your customers on a global scale.

Try FreJun Teler!→

Further Reading – Build Scalable Voice Bot Solutions with APIs

Frequently Asked Questions (FAQ)