When researching stocks, I found myself spending a lot of time reading Reddit and Seeking Alpha posts to understand the main bullish and bearish theses around a company. The problem was less about lack of information and more about filtering and connecting opposing viewpoints.

I built Episteme to scratch that itch.

Given a ticker, it scrapes Reddit and Seeking Alpha discussions and attempts to: - extract investor theses - assign sentiment - surface common bullish and bearish arguments - link criticisms directly to specific theses so counterpoints are easier to evaluate in context

The project is fully open source: https://github.com/amstrdm/episteme

There’s also a small hosted demo here: https://episteme.cloud

This is very much an experiment and still rough around the edges. It started as a personal research tool, not a trading system. NLP quality varies by ticker, sources are limited, and there are plenty of edge cases. I’m mainly interested in feedback on: - whether this framing of “thesis ↔ criticism” is useful - obvious methodological flaws or bias - sources or analysis approaches you’d add or remove - If Episteme (or a slightly altered version of it) would be useful to you

Happy to answer questions or explain how anything works.