JEV Decision Model
A typed AI decision model that scores evidence from filings, news and research by its bearing on an investment question, and turns unstructured reading into a ranked, auditable basis for a decision.
Open a filing, an article or a research page.
The model scores each passage for its bearing on the question.
Export the ranked evidence as Markdown, CSV or JSON.
Analysts read far more than they use. The passages that bear on a decision are buried in filings, news and research.
A typed AI model scores and ranks the text blocks of a page against the question at hand. The result is an ordered evidence set with scores and sources that a reviewer can audit.
Any web page: filings, news or research notes.
Ranked passages with scores and source references, as Markdown, CSV or JSON.
Page content is processed on your machine, and exports are written locally.
Scores measure relevance, not truth. The model cannot see context outside the page, so a person still weighs the evidence.