I build Retrieval-Augmented Generation (RAG) pipelines and AI chatbots that answer questions grounded in your own data — documents, PDFs, knowledge bases, or websites.
What's included:
Document ingestion and chunking pipeline
Vector database setup (ChromaDB or similar)
Retrieval + LLM integration (OpenAI, OpenRouter, or open-weight models)
A working chatbot interface (Streamlit or API endpoint)
I've built and deployed RAG systems for domains like university information assistants and healthcare-focused clinical assistants. I focus on getting you a working, demoable system — not just a proof-of-concept notebook.
Ideal for: internal knowledge bases, customer support bots, document Q&A tools, or research assistants.
I build Retrieval-Augmented Generation (RAG) pipelines and AI chatbots that answer questions grounded in your own data — documents, PDFs, knowledge bases, or websites.
What's included:
Document ingestion and chunking pipeline
Vector database setup (ChromaDB or similar)
Retrieval + LLM integration (OpenAI, OpenRouter, or open-weight models)
A working chatbot interface (Streamlit or API endpoint)
I've built and deployed RAG systems for domains like university information assistants and healthcare-focused clinical assistants. I focus on getting you a working, demoable system — not just a proof-of-concept notebook.
Ideal for: internal knowledge bases, customer support bots, document Q&A tools, or research assistants.