I help businesses design, develop, and deploy production-ready Retrieval-Augmented Generation (RAG) systems powered by Large Language Models (LLMs).

My solutions combine modern AI frameworks, vector databases, cloud infrastructure, and robust evaluation pipelines to deliver accurate, scalable, and cost-efficient AI applications.

What I can build:

• Enterprise RAG chatbots and knowledge assistants • Internal document search and Q&A systems • Customer support AI agents • Multi-document and multi-source retrieval systems • Healthcare and compliance-focused AI solutions • LLM evaluation and monitoring pipelines • AI workflows integrated with existing business systems

Tech Stack:

• Python, FastAPI • LangChain, LangGraph, LlamaIndex • OpenAI, Anthropic Claude, Gemini • AWS (Lambda, ECS, SageMaker, Bedrock) • PostgreSQL, Redis • Pinecone, Weaviate, ChromaDB, FAISS • Docker, GitHub Actions, CI/CD

Deliverables:

• Complete source code repository • API documentation • Infrastructure deployment guide • Evaluation and testing framework • Monitoring and observability setup • Knowledge transfer session

Engagement Process:

Requirements discovery and architecture design

Data ingestion and indexing strategy

RAG pipeline implementation

Evaluation and optimization

Deployment and production readiness review

Handover and support

Whether you need a new AI application or want to improve an existing RAG system, I can help you build a reliable, scalable, and business-focused solution.