Chatbot is a multi-tenant, AI-powered customer engagement platform that enables businesses to provide instant, intelligent support across multiple websites from a single centralized system. The platform leverages Large Language Models (LLMs) to deliver natural, context-aware conversations while helping businesses capture leads, answer customer queries, and automate repetitive support tasks.

As the Backend Developer, I was responsible for designing and developing the core backend architecture, building scalable REST APIs, integrating OpenAI models, and implementing secure authentication and data management. I developed features for conversation management, lead capture, knowledge base integration, chatbot configuration, and live-agent handoff. I also built an administrative portal that allows businesses to manage multiple chatbot instances, monitor conversations, configure AI behavior, and analyse customer interactions.

The platform was developed using Python, Django, Django REST Framework (DRF), PostgreSQL, Redis, Celery, and WebSockets, with integrations to external APIs and CRM systems. It supports asynchronous processing for AI requests, real-time messaging, webhook integrations, and a scalable architecture capable of serving multiple clients simultaneously.

Key features include:

AI-powered conversational assistance using OpenAI models.

Multi-tenant architecture supporting multiple businesses and websites.

Knowledge base integration for accurate, context-aware responses.

Real-time chat with live agent escalation.

Lead capture and customer information management.

Admin dashboard for chatbot configuration, analytics, and conversation monitoring.

REST APIs and webhook integrations for third-party systems.

Background task processing using Celery and Redis for improved performance and reliability.

The platform is designed to help businesses improve customer engagement, reduce support workload, and increase lead conversion by providing 24/7 AI-driven assistance while maintaining the flexibility to seamlessly transfer conversations to human agents when needed.