DCFAlert is a decision-support web app for long-term investors who use DCF models. Instead of calculating intrinsic value or giving investment advice, the app helps users understand when and why their DCF assumptions may need updating. Users follow selected stocks, and the app continuously analyzes new financial reports and company guidance. When new information appears, DCFAlert highlights which core DCF inputs (growth, WACC, terminal growth) may be impacted, provides contextual reference ranges, and explains the reasoning in a calm, analyst-style way. The goal is to reduce guesswork, avoid missed updates, and support better judgment — not replace the investor’s own model.

What was your biggest win?

The biggest win was realizing I needed to pivot from a pure “data monitoring” tool to a judgment-support product. Instead of using 3rd party API's the app generates it's own data pool. I redesigned DCFAlert to focus on assumption review: helping investors understand when new information actually matters for their valuation models.

Project Demo

https://dcfalert.com/

Tools Used