Case Study

Problem

Medicare information can be dense, fragmented, and hard to navigate. A useful assistant needs retrieval grounding, clear citations, and realistic behavior under compute constraints.

Approach

  • Prototype a retrieval-augmented generation workflow over Medicare-related content.
  • Explore chunking, context-window management, embeddings, semantic similarity, and grounding.
  • Evaluate answer quality around source fidelity, failure modes, and practical usefulness.

Outcome

The GitHub profile contains enough material for a concise case study, but the site still needs screenshots, example questions, evaluation notes, and a repository link if public.