Latency is the delay between when you stop speaking and when the AI starts responding. In an AI voice call, this pause determines whether the conversation feels natural or painfully awkward. Under 500ms feels instant. Over 1200ms? People hang up.
Why Latency Actually Matters
Here's the thing about human conversation: we're wired for specific timing.
When someone finishes talking, we expect a response within 200-500 milliseconds. That's not a preference. It's biology. Longer pauses trigger frustration, confusion, even distrust.
In AI voice call systems, the numbers break down like this:
- Under 500ms: Feels instant and natural
- 500-800ms: Noticeable but tolerable
- 800-1200ms: Clearly delayed and frustrating
- Over 1200ms: Conversation falls apart
Miss the timing window, and you've lost the caller. They don't know why the conversation feels "off." They just know it does.
What Actually Creates Latency
Total delay in an AI voice call isn't one thing. It's a chain of processes, each adding milliseconds.
Network Travel Time (10-200ms)
Audio has to get from the caller to the server and back.
- Australian caller to Australian server: 10-30ms
- Australian caller to US server: 150-200ms
Geography matters. A lot. Latency Down Under: Why Local Hosting Matters for AI Voice
Voice Activity Detection (30-100ms)
The system needs to figure out you've stopped talking. Too fast, and it cuts you off. Too slow, and the pause stretches.
What Is VAD (Voice Activity Detection)?
Speech-to-Text (100-400ms)
Your voice becomes text the AI can understand.
AI Processing (200-1500ms)
The language model generates a response. This is the wildcard. Simple answers come fast. Complex ones take time.
Text-to-Speech (100-300ms)
The AI's text becomes audio you can hear.
Network Return (10-200ms)
Audio travels back to your phone.
Add it all up: 450-2700ms total range.
That's the difference between "seamless" and "painful."
The Australian Problem
If you're running an AI voice call system for Australian customers from US servers, you're starting with a handicap.
Using US-hosted AI:
- Minimum 150-200ms network latency each way
- That's 300-400ms gone before processing even starts
- Total latency pushes into the uncomfortable zone
Using Australian-hosted AI:
- Network latency: 10-30ms each way
- Total network overhead: 20-60ms
- Much better foundation for natural conversation
This is why location matters for Australian businesses. You can't optimise your way out of physics. Why Australia Needs Its Own AI Infrastructure
How We Measure It
End-to-end latency: What users actually experience. From speech end to response start.
P50 latency: The median. Half of calls are faster, half are slower.
P99 latency: The worst 1%. This matters because one terrible call sticks with a customer longer than ten good ones.
Consistent moderate latency beats occasional fast responses with random slowdowns.
Making It Faster
Here's what voice AI platforms do to cut latency:
- Streaming: Process audio as it arrives, don't wait for silence
- Response anticipation: Start generating before speech fully ends
- Caching: Store common responses for instant delivery
- Edge deployment: Host servers closer to users
- Model optimisation: Use faster (sometimes simpler) AI models
The Trade-Off You Can't Ignore
Lower latency often means simpler AI. Less processing. Potentially dumber responses.
The goal isn't the fastest possible response. It's finding the sweet spot: low enough latency for natural conversation, high enough quality for useful answers.
That balance is what separates good AI voice call experiences from bad ones.
How Voxworks Handles This
We built Voxworks for the Australian market, which means latency was a design priority from day one.
- Australian data centre hosting
- Optimised processing pipeline
- Streaming architecture
- Local network optimisation
Typical Voxworks latency: 500-700ms—well within the natural conversation range. Bland AI vs Voxworks: Why US Voice Agents Struggle in Australia
Want to see low-latency AI voice calls in action? Start your free trial at voxworks.ai.