ai · 1 min read
Voice Agents: Architecture for Real-Time Speech-to-Speech
Speech-to-speech AI is finally production-ready. Here is the Bhogar AI reference architecture for sub-500 ms voice agents that handle interruptions gracefully.
BABhogar AI TeamProduct & Engineering
Voice is the next great UI for AI agents, but every additional 100 ms of latency makes the experience feel less human. Sub-500 ms round-trip is now achievable with the right architecture, and the gap to production is closing fast.
Why it matters
Most voice POCs fail because they pipe speech through transcription, then a slow text agent, then text-to-speech. The serial latency adds up. Production systems need streaming all the way down and barge-in support so users can interrupt naturally.
How Bhogar AI approaches it
Bhogar AI's voice stack uses streaming ASR feeding directly into a streaming LLM with token-level TTS. A separate VAD detects barge-in and cancels the current generation. The orchestrator runs as a stateful WebSocket session with built-in tool calling and memory.
- Streaming ASR + LLM + TTS pipeline with sub-500 ms median latency
- Voice activity detection and barge-in cancellation
- Per-session memory with summarisation between turns
- PII redaction in transcripts before storage
- Twilio, WebRTC and SIP integrations out of the box
What you get
Contact centres deploying Bhogar AI voice agents handle 60-80% of inbound calls end-to-end, with measurable CSAT parity to senior human agents on tier-1 workloads.