Missing inputs reduce confidence
The model tracks inputs used versus inputs possible. If coverage is thin, the score is confidence-adjusted toward neutral instead of pretending the missing data is bullish or bearish.
Public model notes
TECHi Intelligence is a transparent research layer for quote pages. It combines market, fundamental, analyst, technical, sentiment, leadership, and risk inputs into a confidence-adjusted 0-100 score. The score is directional context, not a guarantee.
The model will keep improving. Every meaningful change gets a version number, a short plain-English note, and a public record so readers can see how TECHi Intelligence is changing over time.
Versioned model
This release documents the first public TECHi Forward methodology: factor weights, confidence adjustment, stance bands, missing-data rules, and reader limitations. Future changes will be logged before they are presented as normal site behavior.
Formula
Composite = 12% technical tape + 12% momentum + 12% track record validation + 14% quality + 11% future value + 10% valuation + 10% analyst/revision + 6% sentiment + 4% leadership + 2% social/developer traction + 7% risk brake. Missing fields pull the final score toward neutral based on model confidence.
Why a 96 differs from a 93
Each factor is normalized to a 0-100 sub-score against the current coverage universe before the weights above are applied, then the confidence adjustment pulls the result toward 50 when inputs are missing. A three-point gap is therefore small and specific: a 96 versus a 93 usually reflects one or two sub-scores — most often valuation pressure (10%) or the risk brake (7%) — sitting a band lower, not a broad difference in quality. Treat neighboring scores as effectively tied and read the factor breakdown, not the single number.
Output bands
These labels describe a research setup. A constructive score can still be wrong, and a high-risk score can still precede a rally. Readers should inspect the factors, confidence level, and source data before relying on any output.
Guardrails
The model tracks inputs used versus inputs possible. If coverage is thin, the score is confidence-adjusted toward neutral instead of pretending the missing data is bullish or bearish.
Rolling validation only appears after enough stored closes and factor snapshots mature. When accuracy tracking is pending, the UI says so.
The written explanation can make a score easier to read, but it does not create the score. The composite comes from the deterministic factor model and the resolved data layer.
TECHi Intelligence is a research screen. It is not a broker recommendation, price target, or personalized investment instruction.
Reader limitation
TECHi Forward scores are informational research tools. They are not personalized advice, trade signals, guaranteed predictions, or a substitute for a broker quote, original filing, exchange feed, or licensed professional review.