TeliSyn AI
An enterprise-grade 24/7 AI voice receptionist engineered with LiveKit WebRTC and Gemini 2.5 Realtime for sub-second conversational latency. Handles inbound telephony via Twilio SIP trunking with dynamic multi-tenant prompt injection and automated call intelligence.
Key Challenges®
//04Building an enterprise telephony system powered by LLMs requires overcoming sub-second voice latency thresholds, real-time interruptions, and seamless multi-tenant isolation.
Sub-Second Audio Latency
Traditional STT-LLM-TTS pipelines add 2-3s delays. We engineered a native bidirectional audio streaming loop using Gemini 2.5 Realtime over WebRTC.
Telephony SIP Integration
Bridging standard carrier phone lines (Twilio SIP Trunking) with self-hosted LiveKit WebRTC media servers on cloud VPS instances.
Multi-Tenant Dynamic Routing
Injecting distinct business knowledge graphs, custom voices, and conversational rules dynamically per inbound phone number.
Natural Barge-In & Interruption
Detecting human speech cues instantaneously to cancel active audio playback without jarring audio artifacts.
Design Approach®
//03We architected a distributed real-time audio pipeline combining cloud telephony with multimodal neural models for instantaneous voice interaction.
Bidirectional WebRTC Worker
Developed a low-footprint Node.js agent worker on @livekit/agents delivering raw PCM audio streams directly to Gemini Realtime API.
Self-Hosted SIP Gateway
Deployed and tuned LiveKit Server and LiveKit SIP Server on Oracle Cloud VPS for deterministic routing and zero audio jitter.
Call Intelligence & Analytics
Automated real-time call transcription, structured sentiment extraction, and CRM sync to MongoDB upon call termination.
Final Outcome
//04TeliSyn AI handles 100% of inbound customer calls autonomously with zero missed calls, sub-500ms response latency, and human-level natural conversation.
Average end-to-end conversational voice latency
Autonomous call resolution without human intervention
Continuous uptime handling concurrent peak call volumes
Customer satisfaction rating on voice naturalness