How to Build AI Voice Agents Using Soundhound?

The quest to create a truly intelligent, conversational AI has led to the rise of incredibly powerful platforms. Among the most advanced is SoundHound, whose proprietary Speech-to-Meaning® and Deep Meaning Understanding® technologies have set a new standard for natural language interaction. For developers, the opportunity to build AI voice agents using Soundhound is compelling. The platform provides a sophisticated “AI brain” capable of powering rich, contextual dialogues across a wide range of digital and physical devices, from mobile apps to in-car assistants.

This is the cutting edge of conversational AI. However, after the initial success of building a brilliant agent, many businesses run into a critical and often insurmountable roadblock. They discover that their intelligent creation is trapped, unable to connect to the most fundamental and trusted channel for customer communication: the telephone. 

This guide will walk you through not only how to leverage the power of SoundHound but also how to solve the crucial infrastructure problem that separates a promising prototype from a scalable, enterprise-ready solution.

What is SoundHound’s Voice AI Platform?

Before diving into the challenge, it’s important to understand what makes SoundHound’s Houndify platform so powerful. It’s an end-to-end conversational intelligence platform that allows developers to build and deploy sophisticated voice assistants. Its key differentiators lie in its proprietary technologies:

• Speech-to-Meaning®: This technology goes beyond simple speech-to-text transcription. It can often understand the meaning of a spoken phrase as it’s being said, leading to faster and more accurate responses.
• Deep Meaning Understanding®: This allows the platform to handle complex, compound queries and understand context in a way that mimics human conversation.

With extensive SDK support for a wide range of platforms (including Android, iOS, React Native, and Python), SoundHound provides all the tools needed to build a brilliant “AI brain.” This is the perfect foundation for creating sophisticated AI voice agents using Soundhound.

The Hidden Challenge: The Telephony Integration Gap

You have successfully used the Houndify platform to build a state-of-the-art AI agent. It’s intelligent, context-aware, and works perfectly in your mobile app. Now, your business wants to deploy this same agent on its 24/7 customer support hotline. This is where the project typically grinds to a halt.

The problem is that the entire ecosystem of tools and SDKs designed for in-app or on-device voice interaction is not built to interface with the Public Switched Telephone Network (PSTN). The global phone system is a completely different world, with its own complex protocols and infrastructure requirements. To make your bot answer a phone call, you would have to build a highly specialized telephony stack from scratch. This involves solving a host of non-trivial engineering problems:

• Telephony Protocols: Managing SIP (Session Initiation Protocol) trunks and carrier relationships.
• Real-Time Media Servers: Building and maintaining dedicated servers to handle raw audio streams from thousands of concurrent calls.
• Call Control and State Management: Architecting a system to manage the entire lifecycle of every call, from ringing and connecting to holding and terminating.
• Network Resilience: Engineering solutions to mitigate the jitter, packet loss, and latency inherent in voice networks that can destroy the quality of a real-time conversation.

Suddenly, your AI project has become a grueling telecom engineering project, pulling your team away from its core mission of building an intelligent and effective bot. The brilliant AI voice agents using Soundhound are trapped in a digital silo.

FreJun: The Voice Infrastructure API for Your SoundHound Agent

This is the exact problem FreJun was built to solve. We are not another AI platform; we do not compete with SoundHound. We are the specialized voice infrastructure layer that provides the missing piece of the puzzle. FreJun allows you to connect your custom-built AI voice agents using Soundhound to the telephone network with a simple, powerful API.

We handle all the complexities of telephony, so you can focus on perfecting your unique AI stack.

• We are AI-Agnostic: You bring your own “brain.” FreJun integrates seamlessly with any backend, including one powered by the Houndify platform.
• We Manage the Voice Transport: We handle the phone numbers, the SIP trunks, the global media servers, and the low-latency audio streaming.
• We are Developer-First: Our platform makes a live phone call look like just another WebSocket connection to your application, abstracting away all the underlying telecom complexity.

With FreJun, you can maintain the full power of the SoundHound platform while leveraging the reliability and scalability of an enterprise-grade voice network.

The SoundHound-Only Approach vs. The Omnichannel Approach with FreJun

Feature	The SoundHound-Only (In-App) Approach	The Omnichannel Approach (SoundHound + FreJun)
Accessibility	Limited to users who have your app installed or are using a specific device.	Universally accessible to anyone with a phone, plus all digital channels.
Use Cases	In-app feature help, smart home control, automotive assistants.	24/7 customer support lines, virtual receptionists, automated phone orders, critical incident support.
Infrastructure Burden	Low. Managed by SoundHound’s SDKs.	Zero telephony infrastructure to build. FreJun manages the entire voice stack.
Customer Journey	Fragmented. A user must switch from a phone call to your app to get automated help.	Unified. A user can interact with the same intelligent assistant across all channels.
Scalability	Scales for in-app user engagement.	Scales to handle thousands of concurrent phone calls.

A Step-by-Step Guide: Building a Complete Voice Agent with SoundHound and FreJun

This step-by-step guide outlines the modern, efficient process for taking your custom-built agent from a device-specific feature to a production-ready telephony deployment.

Step 1: Design and Build Your AI “Brain” with SoundHound

First, use the Houndify platform to build the core intelligence of your agent. This is where you will define its personality, design its conversational flows using custom domains, and leverage SoundHound’s advanced NLU to handle complex queries.

Step 2: Provision Your Telephony Channel with FreJun

Instead of negotiating with telecom carriers, simply sign up for FreJun and instantly provision a virtual phone number. This number will be the public-facing identity for your AI agent.

Step 3: Connect Your SoundHound Backend to FreJun’s API

In the FreJun dashboard, configure your new number’s webhook to point to your backend’s API endpoint. This tells our platform where to send live call audio and events. Our server-side SDKs make handling this connection simple.

Step 4: Orchestrate the Real-Time Conversational Flow

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

1. Receive the raw audio stream from FreJun.
2. Send this audio to the Houndify API for processing by its Speech-to-Meaning® engine.
3. Receive the actionable JSON response from SoundHound, which contains the user’s intent and any extracted entities.
4. Based on this response, your backend logic determines the next step. This might involve making another API call to your internal systems or composing a text response.
5. Take the final text response and send it to your chosen Text-to-Speech (TTS) engine for synthesis.
6. Stream the synthesized audio back to the FreJun API, which plays it to the caller with ultra-low latency.

Step 5: Deploy and Monitor Your Omnichannel Solution

Deploy your backend application to a scalable cloud provider. Once live, use a combination of SoundHound’s analytics to monitor the AI’s performance and FreJun’s analytics to monitor call quality and telephony metrics.

Best Practices for a Flawless Implementation

• Leverage Dynamic Context Management: Take full advantage of SoundHound’s ability to maintain context in multi-turn conversations to create a more natural and satisfying user experience.
• Design for Human Handoff: No AI is perfect. For complex issues, design a clear path to escalate the conversation to a human agent. FreJun’s API can facilitate a seamless live call transfer.
• Secure Your Data: When building AI voice agents using Soundhound, ensure secure handling of user data and API credentials in compliance with all relevant privacy standards.
• Continuously Monitor and Improve: Utilise conversation analytics to gain insight into how users interact with your bot. This data is invaluable for refining your conversational flows and improving intent recognition over time.

Final Thoughts: From a Smart Device to an Enterprise Asset

The freedom to build with a powerful platform like SoundHound is a revolutionary advantage. It allows you to create a truly unique and differentiated conversational AI experience. But that advantage is lost if your team gets bogged down in the complex, undifferentiated heavy lifting of building and maintaining a global voice infrastructure.

The strategic path forward is to focus your resources where they can create the most value: in the intelligence of your AI, the quality of your conversation design, and the seamless integration with your business logic. Let a specialized platform handle the phone lines.

By partnering with FreJun, you can maintain the full power of your custom-built AI voice agents using Soundhound while leveraging the reliability, scalability, and speed of an enterprise-grade voice network. You get to build the bot of your dreams, and we make sure it can answer the call.

Try FreJun Teler!→

Further Reading – The Benefits of Using AI Insight for Call Management: A Comprehensive Guide

Frequently Asked Questions (FAQ)