LLMs & RAG Expertise
Specialized in building enterprise-scale LLM applications with Retrieval-Augmented Generation (RAG). I combine vector embeddings, semantic search, and language models to create intelligent systems that understand context and deliver accurate, personalized responses.
This demo showcases a browser-based LLM system with embedded resume context. The model uses semantic search to retrieve relevant professional experiences and skills, then incorporates them into responses for highly personalized conversations. All processing happens locally in your browser for complete privacy.
What I Offer
Technical Stack
LLM Frameworks
- LangChain
- Prompt Engineering
- Fine-tuning & Adaptation
Vector Databases
- Pinecone
- Weaviate
- FAISS
Cloud & Deployment
- Azure
- AWS Lambda
- REST APIs
Full Stack
- FastAPI/Flask
- React
- Document Processing
Professional Background
Expertise & Specialization
Specialized in building enterprise-scale LLM and RAG applications with proven expertise in production deployment. Expert in combining language models with retrieval systems to create intelligent solutions that deliver measurable business value across diverse domains.
Key Achievements
• Deployed production RAG systems enabling hundreds of users to efficiently query and analyze proprietary knowledge bases
• Built end-to-end NLP pipelines for intelligent document processing and semantic search across large repositories
• Created conversational interfaces combining fine-tuned language models with retrieval mechanisms for accessible knowledge access
LLMs & RAG Demo
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