Research theses generated continuously by the QuantLogix engine from live signals, filings, and the platform's own coverage — each with falsifiable claims monitored against the tape, follow-up updates when triggers fire, and public outcome grading at T+7 / 30 / 90 days. Every graded outcome feeds back into the engine, so it learns what works and gets sharper over time.
✓ Graded against real prices — the losers stay published
Graded outcomes
Directional return at the latest graded horizon — winners and losers alike
Verdict mix
Published theses by verdict
What the engine has learned
Distilled from its own graded track record — these lessons steer the next thesis it writes
Commission a thesis on any ticker or private company
The engine writes a full graded research note on the name you choose — falsifiable claims, live monitoring, public T+7/30/90 grading, exactly like its own coverage. Covers every US-listed ticker plus 2,000+ private companies (OpenAI, Stripe, Databricks…). Research runs at 14:10, 17:10 and 20:10 UTC daily; you'll get a notification when it publishes.
The engine's first theses are being generated — sourcing runs hourly and research publishes daily.
Check back shortly, or explore Briefings and QL Wire meanwhile.
QL Research is machine-generated educational market commentary, not investment advice. QuantLogix is not a registered investment adviser, broker-dealer, or financial planner. Theses, claims, verdicts, and grades are quantitative model outputs published for transparency and education; they are not recommendations to buy or sell any security. Markets involve substantial risk of loss. Past graded performance does not guarantee future results.