AI Cold Calling Agent (LangDB AI Buildathon)

🚀 An AI-powered cold calling agent using Express, React (TypeScript), Node.js, LangChain (Gemini API), and LangDB to automate sales and customer interactions.

Features

✅ AI-powered conversations using LangChain + Gemini API
✅ Call transcript storage & retrieval using a dedicated database
✅ Real-time call monitoring with React + TypeScript UI
✅ Sentiment analysis & lead classification
✅ Twilio integration for voice calls
✅ Auto follow-up scheduling

Tech Stack

• Frontend: React + TypeScript
• Backend: Express + Node.js
• AI Layer: LangChain + Gemini API
• AI Gateway: LangDB (for enhanced AI interactions)
• Database: MongoDB / PostgreSQL (for call transcript storage)
• VoIP: Twilio (for real calls), Coqui TTS - voice training

Project Structure

Backend (server/)

models/Call.js: Defines the call schema (if using a database).
services/:
database.js: Handles database connection.
langchain.js: Manages AI interactions with LangChain + Gemini API.
twilio.js: Integrates Twilio for voice calls.
index.js: Likely the main Express server.
Frontend (src/)

components/CallDashboard.tsx: UI for monitoring live calls.
services/api.ts: Handles API calls to the backend.
types/Call.ts: Defines TypeScript interfaces for calls.
vite-env.d.ts: Vite environment configuration.
Config & Environment Files

.env.example: Example for environment variables.
.gitignore: Ensures sensitive files aren’t pushed to GitHub.
tailwind.config.js: Tailwind CSS setup.
tsconfig.json: TypeScript configuration.
eslint.config.js: Ensures clean coding standards.

Installation

Backend Setup

cd backend
npm install
npm start

Frontend Setup

cd frontend
npm install
npm start

Usage

1. Start the backend server.
2. Start the frontend app.
3. Use the dashboard to monitor AI calls in real-time.

Future Enhancements

• 🔹 Multi-language support
• 🔹 More AI-driven insights
• 🔹 CRM integration