A probability-calibrated ML engine for stock selection, rigorous dividend screening for income portfolios, and end-to-end encrypted household retirement planning. Honest numbers, live track record, and zero-knowledge privacy on your financial data — all in one tool.
Not one signal. Three independent rankings calibrated for different holding periods — so you can size your portfolio across conviction levels and time horizons.
The same data science approach extended across the whole retirement lifecycle: dividend-stock screening, payout modeling, and household-level retirement planning with tax-aware withdrawals and end-to-end encrypted storage. Built for retirees, near-retirees, and anyone serious about their financial future.
Every pick includes probability, expected value, uncertainty bands, a stop loss, a sell target, and broker-ready copy. No guessing what the model thinks.
Illustrative example. Real picks are updated from the nightly pipeline and include live prices, stop-loss ratcheting, and historical re-recommendation tracking.
No black box, no "proprietary AI" hand-waving. Here's what's actually happening under the hood.
P(up) · r_up + (1−P) · r_down — the probability-weighted return across both outcomes. Not the degenerate formula that ignores downside.
Access is currently invite-only. Request access to receive a code when a spot opens, or sign in if you already have one.
The platform now frames each model output as historical setup reliability, forecast range, factor attribution, regime context, and portfolio risk — not as an oracle prediction.