# AI Calling Platform - Case Study | Lumeor Studio

> A platform where users can call a phone number and talk to an AI assistant. Every interaction is logged, structured, and ready for analytics.

Case Study • Voice AI

# AI Calling Platform

Call-In Voice AI Assistants | Twilio + LLM

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Project Overview

A platform where users can call a phone number and talk to an AI assistant. Every interaction is logged, structured, and ready for analytics.

## The Product Story

Instead of forcing users into a web chat, this platform lets them dial a number and talk to an AI in natural language.

This turns any phone into a smart, AI-enhanced communication channel — without apps, logins, or friction.

### Key Capabilities

-   Dial a phone number
-   Talk to an AI in natural language
-   Hear real-time, natural-sounding responses
-   Structured conversation logging

## The Challenge

Delivering low-latency, real-time responses over voice while managing streaming text-to-speech.

-   Low-latency voice response
-   Streaming STT and TTS
-   Persisting conversations with clear schema
-   Handling call drops and timeouts

## Solution Delivered

### Architecture

-   Twilio Voice for telephony
-   Speech-to-text + LLM + TTS pipeline (Azure/OpenAI)
-   Node.js backend for orchestration
-   Firebase/Firestore for conversation storage

### Key Features

-   Real-time AI conversation with streaming
-   Structured logging (speaker, text, timestamp)
-   Final 'save on hang-up' logic
-   Hooks for sentiment analysis and tagging

## Results & KPIs

✓ Reusable voice AI infrastructure for multiple use cases

✓ Latency low enough to feel conversational

✓ Robust data storage for CRMs and training

#AI calling platform#Twilio GPT integration#voice AI agent#phone-based AI assistant#call center automation

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Source: https://www.lumeor.studio/case-studies/ai-calling-platform/