Overview
This dummy project outlines a retrieval service meant to sit between raw documents and downstream applications. The idea is to keep search behavior understandable, fast enough for repeated use, and simple to reason about when relevance starts drifting.
Problem
Internal search often becomes a stack of disconnected heuristics. Embeddings help, but they can also hide ranking decisions behind vague similarity scores. Teams end up with results that feel magical when they work and frustrating when they fail.
Approach
The system separates ingestion, indexing, retrieval, and reranking into clear stages. That keeps it easier to test ranking behavior, inspect failures, and decide when a change is helping versus merely moving errors around.
Outcome
As a portfolio entry, the project demonstrates how I think about practical infra work: fewer hidden assumptions, clearer ranking logic, and a structure that can expand into production use without losing legibility.