Methodology

How NorrisAI AlphaLens works

What NorrisAI AlphaLens is

NorrisAI AlphaLens runs any US-listed stock through 15 named research frameworks and returns a finished, plain-English write-up. It's built and run by one person in Memphis, TN. It is not an investment adviser, broker-dealer, or fiduciary, and nothing it produces is a recommendation to buy or sell.

What we analyze

US-listed equities only. Enter a ticker, pick a framework — or run all 15 — and AlphaLens pulls current data and produces a structured analysis in plain English, not a table of numbers to interpret yourself.

Data sources

Every write-up draws on three live sources at the time you run it: current market prices, SEC EDGAR filings, and current news search. AlphaLens does not answer from AI training data alone — if live data isn't available for a given data point, the framework says so rather than filling the gap.

How a write-up is produced

You choose a ticker and a framework (or Run All 15). AlphaLens pulls the current price, relevant SEC filings, and recent news, then runs that data through the selected framework's analysis structure. The output is a single write-up — not raw data, not a chat answer, a structured research document.

The 15 frameworks

  1. Full Company Breakdown — Complete business overview: what the company does, how it makes money, and where it stands in its market.
  2. Bull vs Bear + Moat Analysis — A balanced case for both sides, with a structured assessment of competitive advantages and how durable they are.
  3. Fair Value Stress Test — Multiple valuation approaches run under different scenarios — optimistic, base, and bear case. Publishes dated bull/base/bear figures inside the write-up; does not publish a live price target, an "undervalued" percentage, or a buy/sell call.
  4. Earnings Quality Analyzer — Checks for accounting red flags, revenue quality issues, and whether reported earnings match actual cash generation.
  5. Long-Term Investment Thesis — A 3–5 year conviction case with built-in invalidators: what would prove the thesis wrong.
  6. Portfolio Risk & Fit — Correlation, concentration, and stress-testing for how the stock fits an existing portfolio.
  7. Trading Journal Audit — Behavioral pattern analysis and coaching drawn from your own trade history.
  8. Insider Activity Analyzer — What executive buying and selling actually signals, separating routine transactions from meaningful ones.
  9. Catalyst Calendar — Upcoming events — earnings, launches, regulatory decisions — rated by probability and potential price impact.
  10. Options Flow Analyzer — What options-market positioning signals about a stock.
  11. Competitor Moat Comparison — Head-to-head competitive advantage analysis against top rivals.
  12. Management Quality Scorecard — Track record, capital allocation skill, compensation alignment, and guidance accuracy.
  13. Macro Sensitivity Analysis — How interest rates, inflation, dollar strength, and economic cycles affect the stock.
  14. Revenue Quality Decomposer — Recurring vs one-time, organic vs acquired, pricing vs volume — how durable the growth actually is.
  15. Short Squeeze Probability — Short interest, days to cover, borrow cost, and squeeze-setup conditions, without the hype.

Provenance and dating

Every write-up is tied to the moment it was run. Sample write-ups on the site show the date they were generated and are not updated in real time — prices, filings, and news move after that date. A live run in the app pulls current data at the moment you run it.

Limits of AI output

AlphaLens is built on AI models and current data feeds, not a human analyst. It can misread a filing, miss context, or be wrong. It works from live filings and pricing data rather than invented numbers — if the data isn't there, it says so — but the output should be checked against the source material, not taken as fact.

What we do not do

How to read a write-up

Start with the run date and data sources at the top — know what the write-up saw and when. Read it as one framework's structured take on the available data, not a verdict. Cross-check anything that would change your decision against the primary source (the filing, the price feed, the article) before acting on it.

NorrisAI AlphaLens is a research tool, not investment advice. Not a registered investment adviser, broker-dealer, or fiduciary. AI output can be wrong. You own the decision.