SherpaQuant.ai
AI ALPHA v3 is a probability-weighted research workflow built from evidence-covered factor families, payoff asymmetry, data freshness, and explicit risk context. Scores are research tools, not investment advice. When inputs are missing, SherpaQuant.ai surfaces insufficient data rather than guessing with zeros.
A research workflow that scores opportunities and tells you, honestly, when it lacks the data to do so.
Each score carries dataCompleteness and confidence in the engine payload. UI must downgrade certainty when coverage is partial. Redis/Hermes keys are listed in docs/HERMES_REDIS_CONTRACT.md.
The in-app Why panel mirrors the same pillar breakdown and timestamps as the narrative engine inputs. Every claim in AI memos should trace to a handler-backed field or an explicit "unavailable" branch.
Historical simulations shown in-app must label in-sample vs out-of-sample windows and include prominent disclaimers. Past performance does not guarantee future results.
SherpaQuant.ai provides analytics and research tooling only. Nothing here is an offer, solicitation, or personalized investment advice. You are responsible for your own decisions and compliance obligations.
The AI-ALPHA score reads as a number in a tier badge, always paired with an IN VALIDATION marker.
IN VALIDATION