AI-Assisted Literature Review

The work

A systematic literature review on gender equity in higher education — over 200 peer-reviewed articles in English and Spanish. Manually coding each one across multiple analytical dimensions was going to take months. I built a classification pipeline that compressed the work into hours without giving up rigor.

Framework

A document analysis classified by themes, adapted to the specific topic of each research project. The analytical fields are designed to fit the research question — what counts as evidence, what gets compared, what gets left out — and applied consistently across the whole collection.

What the client got

A structured dataset, ready for synthesis. A reusable framework — the same pipeline runs on any new literature review with minimal reconfiguration. Bilingual articles in, consistent output in the language the researcher needs. Human review stays in the loop for flagged cases.