Model transparency
How Qualtix builds, tests, explains, and monitors its stock model
Review the evidence layers behind the model, data sources and safeguards, historical validation controls, live forward tracking, known limitations, AI boundaries, and founder accountability.
Transparency matters because Qualtix is a financial research product. Users should be able to see what the system calculates, what AI explains, what is tested historically, and where the model can fail.
The Qualtix model is rules-based. AI is used to explain and organize model output; it does not replace the deterministic score or silently invent a verdict.
What AI Does
- Explains model output in plain language.
- Helps summarize business quality, valuation, timing, concerns, and portfolio context.
- Helps users ask follow-up research questions about the model result.
What AI Does Not Do
- It does not create the underlying score.
- It does not override the deterministic verdict.
- It does not place trades, manage money, accept deposits, or act as an investment adviser.
- It does not know future news, future filings, or future stock prices.
Known Boundaries
- A high-quality business can still be overpriced.
- A cheap stock can still be low quality or risky.
- Entry timing can change quickly when price or market conditions move.
- Filing timing and third-party data quality can affect the available inputs.
Read The Proof Chain
Qualtix is for research and education only. It is not financial advice.