The release of OpenAI's Realtime API has redefined the landscape for voice agents. We have moved past the sluggish "transcribe-wait-respond" loop into fluid, interruptible conversations that feel genuinely human.
However, for engineers and product leaders, this creates a new infrastructure challenge: How do you transport audio from the telephone network to OpenAI efficiently enough to support real-time interaction?
At Wavix, we see two primary paths. Neither is inherently "better"; they simply serve different architectural strategies. Here is how to decide which fits your project.
Path 1: Integration via SIP Trunking
Best for: Teams prioritizing compatibility and speed to market.
This is the standard approach. If you aren't interested in building a custom audio transport layer, use standard telephony protocols to connect your calls.
Wavix manages global carrier origination and interconnects, delivering the active call leg to your endpoint. This ensures low-latency connectivity while your system retains full control over the conversation logic.
This is ideal if you are integrating into an existing contact center or PBX that already speaks SIP, or if you are using an AI orchestration platform.
Technical Snapshot:
- Protocols: Standard SIP over UDP, TCP, or TLS for signaling.
- Codecs: Full support for G.711 (PCMA/PCMU) and G.729, ensuring compatibility with OpenAI’s SIP.
- Security: TLS for signaling and SRTP for media encryption ensure data security in transit.
Explore our SIP Trunking Guides at docs.wavix.com →
Path 2: Integration via Call Media Streaming
Best for: Developers building proprietary voice bots requiring granular control.
This is the custom approach. It is designed for complex logic—such as detecting "barge-in" interruptions - or when you need to fork audio to OpenAI while simultaneously streaming it to a compliance recorder or sentiment analyzer.
This approach creates a “tunnel” between the phone call and your server. Wavix forks the raw audio and streams it directly to your application in real-time. You then write the code to forward that audio to OpenAI, giving you complete freedom to manipulate the audio stream before it leaves your perimeter.
Technical Snapshot:
- Protocol: Secure WebSockets (wss://) for real-time bidirectional transport.
- Data Format: Raw audio streamed as base64-encoded PCM payloads.
- Latency: Engineered for sub-100ms internal processing to keep the in-call latency to the absolute minimum.
Note: Get the full technical breakdown in our article on Call Media Streaming.
Learn how to start a Media Stream at docs.wavix.com →
Which architecture is right for you?
For most organizations, this decision is dictated by existing infrastructure rather than preference.
- Choose SIP Trunking if you have a Contact Center or PBX. If you are adding AI capabilities to an existing platform (e.g. 3CX), SIP allows you to route calls to your AI agent without a "rip and replace" of your stack. It is the fastest to bridge your AI voice agent to the PSTN.
- Choose Media Streaming if you are building a custom application. If you are developing a proprietary voice bot from scratch (using Python, Node.js, or Go) and do not need to interface with a legacy phone system, this is your best choice. It removes the "black box" of third-party platforms, offering lower latency and raw access to the audio stream.
How Wavix fits in
We don't prioritize one method over the other. Our network is built to support both standards with carrier-grade reliability.
Whether you need to trunk a thousand concurrent lines into a global contact center or open secure WebSockets for a new AI agent, we provide the infrastructure to make it work.
Ready to bring your voice agent to life? Check out the setup guides at docs.wavix.com
