RAG Developer

RAG Developer for Retrieval-Augmented Generation Systems

My RAG work focuses on making AI answers more reliable by retrieving the right source material, organizing context well, and keeping outputs connected to the user's actual knowledge base.

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What I Can Build

  • Chunking and indexing documents for semantic retrieval.
  • Using embeddings, FAISS, ChromaDB, Qdrant, and vector search workflows.
  • Combining OCR and RAG for handwritten or scanned learning material.
  • Designing grounded question answering, summarization, and study workflows.

Focus Keywords

These are the areas this page represents in a natural, portfolio-first way.

RAG DeveloperRetrieval-Augmented GenerationVector SearchEmbeddings

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Relevant Projects

SmartNotes AI project preview Static preview

SmartNotes AI

Handwritten Notes RAG Assistant

SmartNotes AI turns handwritten notes into a searchable study assistant using OCR, embeddings, retrieval, and AI summaries.

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Read Case Study-> View Code->
MediSwap project preview Live Space

MediSwap

Semantic Medicine Recommendation System

MediSwap finds composition-based medicine alternatives with fuzzy matching, semantic search, FastAPI, Qdrant, and embeddings.

FastAPIQdrantBGE EmbeddingsRapidFuzzSemantic Search
Read Case Study-> View Code->