AI Support Copilot
Production AI support copilot with RAG, streaming responses, evaluations, and admin tooling serving thousands of customer conversations every day.
Production RAG support system with streaming answers, evaluations, and human handoff tooling. It handles the majority of repetitive support load without degrading answer quality.
Built with
“The chatbot handles 80% of our support tickets autonomously. It paid for itself in the first month.”
Priya S.
Head of Support Operations
The Challenge
The client needed support automation that could answer product questions accurately, stay grounded in documentation, and scale during peak traffic without turning support into an unreliable AI experiment.
The Solution
I shipped a production-grade RAG system with streaming responses, evaluation hooks, fallback flows, and the internal tools required to manage knowledge quality. The result was a support copilot the team could monitor, improve, and trust in production.
Key results
Resolved without human intervention
P95 including retrieval and generation
With autoscaling across peak support windows
Stack
Timeline
Week 1
Architecture design, model selection, retrieval evaluation, and support flow mapping
Week 2-4
Core chatbot engine, embedding pipeline, streaming API, and fallback logic
Week 5-6
Admin dashboard, analytics, quality scoring, and production deployment
Project Details
Technical implementation and architecture overview
Grounded retrieval and evaluation
Custom embedding pipeline with semantic search across structured and unstructured knowledge. Evaluation workflows catch weak retrieval and answer-quality regressions before they hit customers.
Streaming support architecture
FastAPI backend with token streaming, handoff logic, rate limiting, and conversation memory for multi-turn support requests under production load.
Admin tooling and QA analytics
Built internal dashboards for managing sources, reviewing conversations, and flagging risky answers so the support team could improve the system continuously.
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? +
TypeScript, 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.