Real-Time Streaming with Amazon Nova Sonic: Architecture Deep Dive
MDFit Nova-Sonic handles live phone calls, which means every millisecond of latency is perceptible. Here is how we architected the system for real-time streaming.
The Latency Budget
For natural conversation, teams often target around a 1-second response window where feasible. A practical budget can look like:
- Speech-to-text: ~200ms
- Intent classification + routing: ~100ms
- LLM generation: ~400ms
- Text-to-speech: ~200ms
When latency drifts too high, callers perceive the assistant as less responsive and escalation rates tend to increase.
Bidirectional WebSocket Architecture
Amazon Nova Sonic supports bidirectional streaming over WebSockets. This is critical because it allows:
Simultaneous input and output
The system can process incoming audio while generating a response. This enables natural turn-taking and even mid-sentence interruption handling.
Streaming token generation
Instead of waiting for a complete response, tokens stream to the TTS engine as they are generated. The first syllable of the response begins playing while the rest is still being generated.
Barge-in detection
If a caller interrupts the AI mid-response, the system detects the barge-in, stops the current response, and processes the new input.
The Twilio Integration
Twilio Media Streams provides the raw audio bridge between the phone network and our WebSocket server.
Caller → Twilio → Media Stream → WebSocket → Nova Sonic → WebSocket → Media Stream → Twilio → Caller
Each hop adds latency, so we colocate our WebSocket server in the same AWS region as the Nova Sonic endpoint.
Optimization Techniques
Connection pooling
Nova Sonic WebSocket connections are expensive to establish. We maintain a warm pool of connections that are reused across calls.
Audio chunking
We send audio in 20ms chunks — small enough for responsive processing, large enough to avoid excessive network overhead.
Response prefetching
For common intents (greeting, hold, transfer), we pre-generate responses and cache the audio. This drops response time to under 200ms for predictable interactions.
Results
With these optimizations, recent monitoring windows have shown sub-second median responses on core paths and low-latency p95 performance for most calls.
For related architecture patterns, explore Blog, review MDFit, and see broader implementation tracks on Solutions.