AI Chatbot Platform
Production AI chatbot with LLM integration, RAG architecture, and real-time streaming. Handles thousands of customer queries daily with 95%+ accuracy.
Case study
AI Chatbot Platform
Production AI chatbot with LLM integration, RAG architecture, and real-time streaming. Handles thousands of customer queries daily with 95%+ accuracy.
Production AI chatbot platform with LLM integration, RAG architecture, and real-time streaming serving thousands of queries daily.
The Challenge
The client needed an intelligent customer support system that could handle complex queries with high accuracy, integrate with their existing knowledge base, and scale to thousands of concurrent users without degradation.
The Solution
We built a production-grade AI chatbot with retrieval-augmented generation (RAG), real-time streaming responses, and a custom fine-tuning pipeline. The system integrates with multiple LLM providers and includes admin tooling for managing knowledge bases and monitoring conversation quality.
Key results
Measured against human baseline
P95 including retrieval + generation
With auto-scaling infrastructure
Stack
Timeline
Week 1
Architecture design, LLM evaluation, and RAG pipeline prototyping
Week 2–4
Core chatbot engine, embedding pipeline, and streaming API
Week 5–6
Admin dashboard, monitoring, and production deployment
“The chatbot handles 80% of our support tickets autonomously—it paid for itself in the first month.”
Project Details
Technical implementation and architecture overview
RAG-powered knowledge retrieval
Custom embedding pipeline with semantic search across structured and unstructured data. Automatic chunk optimization and relevance scoring ensure accurate, grounded responses.
Real-time streaming architecture
FastAPI backend with WebSocket streaming delivers token-by-token responses. Built-in fallback chains, rate limiting, and conversation memory for contextual multi-turn interactions.
Admin tooling + analytics
SvelteKit dashboard for managing knowledge bases, reviewing conversations, and tracking accuracy metrics. Automated quality scoring flags conversations that need human review.
FAQs
How much does it cost? +
Complete projects start at $2,000. I give you a fixed price after a free 30-minute call — no hourly billing, no surprise invoices.
How fast can you deliver? +
Most MVPs go live in 2–4 weeks. Larger projects run in 2-week sprints with a live demo every week so you always see progress.
Who will actually build my product? +
Me. Personally. I have 10+ years of experience and I handle everything — frontend, backend, infrastructure, deployment. No outsourcing.
What makes you different from agencies? +
No overhead. You talk directly to me — the person writing the code. That means faster decisions, better output, and lower cost.
What if I need changes after launch? +
You get 30 days of free post-launch support included. After that, I offer affordable monthly retainers or project-based work.
What technologies do you use? +
SvelteKit, React, FastAPI, Node.js, Python, Rust, Solidity, React Native, Flutter — I pick what fits your project, not what's trendy.
Can one person really handle everything? +
Yes. Frontend, backend, infrastructure, mobile, and Web3. With 10+ years of experience and AI-accelerated workflows, I consistently deliver what agencies need 10 people to build.
Do you use AI to write code? +
Yes. I use AI as a force multiplier — for code generation, review, testing, and documentation. It's why I ship 3x faster than traditional developers. But every line is reviewed, tested, and refined by me before it touches your project.
Is your code production-ready? +
Yes. Every project I deliver is production-grade — tested, optimized, secure, and deployed to real infrastructure. I don't hand off prototypes. You get code that's ready for real users from day one.
What if my project doesn't work out? +
You own everything I build — every line of code, every design file. If you want to walk away or bring in another team, you can. No lock-in.