AI Chatbot Platform · LLM Integration
Production-ready AI chatbot platform with LLM integration, RAG architecture, and real-time streaming for intelligent customer support.
Case study
AI Chatbot Platform · LLM Integration
Production-ready AI chatbot platform with LLM integration, RAG architecture, and real-time streaming for intelligent customer support.
Built a production-ready chatbot platform with LLM integration, RAG architecture, and real-time streaming for customer support.
The Challenge
The client needed a production-ready AI chatbot for customer support but lacked the expertise to integrate LLMs, implement RAG architecture, and handle real-time streaming at scale.
The Solution
Built a complete chatbot platform with FastAPI backend, LLM integration, RAG for accurate responses, and real-time streaming. The system handles high traffic with sub-2-second response times and maintains high accuracy through proper context management.
Key results
Response accuracy rate
Average response time
Active users
Stack
Timeline
Week 1–2
Requirements gathering, LLM selection, and architecture design
Week 3–6
RAG implementation, vector database setup, and API development
Week 7–8
Real-time streaming, monitoring, and production deployment
“The chatbot reduced support ticket volume by 70% while maintaining high customer satisfaction.”
Project Details
Technical implementation and architecture overview
RAG architecture
Implemented retrieval-augmented generation with vector embeddings, semantic search, and context management for accurate responses.
Streaming responses
Built WebSocket-based streaming for real-time token generation, providing instant feedback to users.
Monitoring & analytics
Set up comprehensive monitoring, A/B testing framework, and analytics dashboard for continuous improvement.
FAQs
What do you build? +
Web3, AI, Systems, Web. End-to-end. One person. From idea to deployed.
Do you do consultancy? +
Yes. Architecture, stack selection, code reviews. Hourly or contract. Get unstuck fast.
How fast can you deliver? +
Fast. I focus on going live. Less bureaucracy, more shipping. Let's discuss timeline.
One person for everything? +
Yes. Frontend, backend, infrastructure, deployment. Complete systems. End-to-end.