college essay vector grader

uses vector embeddings to compare essay drafts against successful essays with live distance-to-target metrics. the transparency of showing "how far am I from good" is the novel UX — unlike LumiSource and GradGPT which grade essays using AI trained on successful essays but don't expose vector embeddings or distance metrics to the user.

needs a corpus of successful essays (legally tricky). the embedding visualization is the differentiator. could use open-source embedding models. connects to the precision description engine for the writing quality improvement angle and to OnCue for the application writing use case.

spreadsheet evaluation: originality 7/10, excitement 7/10, MVP 2-4 weeks. tech depth 5/10, labeled [WRONG FIT] ("embeddings + cosine similarity — could be done in a weekend, not a month").

timeline

• [2026-04-10] captured from google sheets — 7/10 originality, 7/10 excitement, [WRONG FIT] tier