AI Voice Calling Automation
Conversational Sales Assistant
Conversational AI · Automation
System design, dialogue orchestration, sentiment pipelines, data pipelines
Private production project · Presented at eChai Demo Day
Overview
An event-driven AI voice automation platform built on the Twilio Voice API that places real-time outbound calls, holds an adaptive conversation, reads sentiment and hands over to a human a[...]
The challenge
Voice is unforgiving: every turn is a race between speech recognition, intent handling, synthesis and telephony state. The system needs to decide, mid-call, whether to continue, branch or [...]
Contribution
- Built an event-driven AI voice automation platform on the Twilio Voice API enabling real-time conversational outbound calling with adaptive dialogue orchestration.
- Engineered sentiment-aware response pipelines with automated call-flow decision logic and intelligent human-agent escalation routing during live interactions.
- Designed structured conversation logging pipelines on Supabase supporting analytics-ready datasets and Twilio call lifecycle state management.
- Presented a live demonstration of the system to 50+ attendees at eChai Demo Day.
Architecture & workflow
How the system moves from input to outcome.
Core features
Adaptive dialogue
Conversation branches based on what the caller actually says.
Sentiment awareness
Response pipelines factor in tone, not just content.
Human escalation
Routing to a human agent when the call needs one.
Lifecycle management
Twilio call state tracked end to end.
Conversation logging
Structured transcripts and events stored for later analysis.
Analytics-ready data
Supabase schemas designed for downstream reporting.
Technical highlights
- Event-driven architecture built around telephony callbacks.
- Sentiment-aware decision logic operating inside a live call.
- Analytics-ready conversation datasets from day one.