I build practical AI systems and backend applications, mostly with Python.
My work sits around LLM applications, RAG, AI agents, data analysis, and the backend systems that make them usable beyond a simple demo.
I like taking an idea from a basic concept to something that actually works — connecting models to data, APIs, databases, and tools rather than treating an LLM as a standalone chatbot.
Some of my current work includes:
A multi-RAG university assistant built around document retrieval and question answering, using FastAPI, PostgreSQL, FAISS, Sentence Transformers, and LLMs.
Focus: RAG · Retrieval · LLM Applications · Backend
A FastAPI-based LLM application with persistent conversation memory, SQLAlchemy, and SQLite.
Focus: LLM Integration · APIs · Backend · Conversation Memory
An AI system that combines natural-language interaction with data profiling, statistical analysis, grouping, anomaly detection, and tool-based workflows.
Focus: AI Agents · Tool Use · Data Analysis · LLM Applications
Languages Python · SQL · Java · C++
AI & Data LLMs · RAG · AI Agents · Machine Learning · Pandas · Data Analysis
Backend FastAPI · SQLAlchemy · REST APIs
Databases PostgreSQL · SQLite · MySQL · Oracle
Tools Git · GitHub · VS Code
AI agents that can reason through tasks, use tools, work with structured data, and maintain useful context across interactions.
I'm particularly interested in the space between AI models and real software systems — where models have to work with APIs, databases, retrieval systems, and application logic.