Under 500ms: How to Architect Ultra-Low Latency Voice Agents

The biggest killer of AI voice adoption is the "Awkward Silence."

In a human conversation, the average response gap is about 200ms. If an AI takes 2 seconds to respond, the human brain perceives it as a failure. The user thinks the AI didn't hear them, they start talking again, and suddenly both parties are talking over each other.

At Butter AI, we obsessed over reaching the sub-500ms threshold. Here is how we built our Real-time Pipeline—the system that manages the "handshake" between hearing, thinking, and speaking.

1. Thinking While Listening

Most platforms wait for a user to finish their entire sentence before even starting to process it. That adds a "dead air" penalty that makes the AI feel slow.

The Butter Way: Incremental Hearing Our system doesn't wait for you to finish. It starts analyzing the intent while you are still speaking. By the time you take a breath, the "brain" of the AI is already warmed up and ready to respond.

2. No More "Generating..." Delays

Standard AI models generate text word-by-word. If you wait for a full paragraph to be written before the AI starts speaking, you've already lost the user.

The Butter Way: Just-in-Time Speaking We treat the AI's thoughts like a stream. As soon as the first few words are ready, we send them to the voice engine immediately. While those first words are being spoken to the user, we continue generating and preparing the rest of the sentence in the background. It’s a seamless hand-off that eliminates the "loading" feel.

3. Handling Interruptions Naturally

The hardest part of voice AI isn't speaking—it's knowing when to stop. In a real conversation, humans interrupt each other.

The Butter Way: Instant Flush Our pipeline is built to be "alert." The millisecond our system detects you speaking, it sends an instant "Stop" signal. This clears the AI's current thoughts and stops the voice mid-sentence, allowing the agent to listen to your new input immediately. No awkward talking over each other.

The Latency Budget Breakdown

Here is what a typical "Budget" for a <500ms response looks like in our infrastructure:

Conclusion

Ultra-low latency isn't solved by one "fast" model. It’s solved by tight coordination between every layer of the stack. When you build on Butter AI, you aren't just getting an API; you're getting an architecture that has been tuned to ensure your agents never miss a beat.

Ready to build a "snappy" agent? Explore our technical docs or try the demo to hear the sub-500ms response times for yourself.