Retrieval and Reasoning Systems

Developed workflows that combine language models, retrieval, validation, tool execution, and structured actions across heterogeneous data sources. These systems connect natural-language interfaces to reliable downstream workflows by grounding model outputs in retrieved context, schemas, and executable tools.

Focus areas: retrieval-augmented generation, tool-calling, structured outputs, orchestration, validation, heterogeneous data integration

Technologies: Python, LLMs, RAG, vector search, knowledge graphs, SPARQL, LangGraph-style orchestration, schema validation