AI & RAG Integration in Kuwait
I build AI features that are actually useful — grounded in your own content with retrieval-augmented generation (RAG), not a chatbot that makes things up. I've shipped RAG-based AI tutoring in production that raised engagement 40%.
Bolting a raw LLM onto a product gives confident, wrong answers. RAG grounds the model in your real documents and data, so the AI answers from what your business actually knows — the difference between a demo and something you can put in front of users in Kuwait.
What you get
- RAG pipelines that ground answers in your documents and data
- LLM-powered features: search, summarization, assistants, tutoring
- Integration into your existing web or mobile app and backend
- Guardrails and evaluation so quality is measured, not assumed
- Cost and latency tuning for the model calls
How I work
- Start with one high-value use case and prove it
- Ground the model in real data and measure answer quality
- Ship behind a flag, watch it, then expand
Tech stack
RAGLLM APIsPythonNode.jsVector search
Related work
Want to add AI to your product in Kuwait?
Tell me what you'd want the AI to do — I'll reply within a day with what's realistic.