Confident recommendations
A patent-pending gating layer on your sequential backbone — blend in extra structure when the session has support; fall back to your model when it does not.
Move your cursor — confidence crystallizes near the probe.
Lattice sits on the backbone you already ship. A binary ON/OFF switch decides whether an auxiliary scoring path gets blended in — not whether items disappear from the list.
LSTM, transformer, SASRec — any sequential ranker you already train and serve. Lattice never replaces it.
When confidence is below threshold, the gate stays OFF. Rankings match your backbone exactly — auditable, not quietly down-weighted.
When ON, archetypes fit in your backbone's embedding space and fusion kicks in. Always-on fusion scores higher on pooled benchmarks; gating trades peak HR for control you can explain.
MovieLens primary eval: 30 paired seeds, full-catalog ranking, same test rows every seed. Lifts are vs each backbone alone — not vs published SOTA. Want to reproduce independently? LorianBannis@banlys.com.
| Backbone | Dataset | Gated lift (HR@10) | Ungated lift | Seeds | Note |
|---|---|---|---|---|---|
| LSTM | MovieLens | +31.7% | +58.7% | 30 | Headline result |
| Transformer | MovieLens | +13.3% | +20.9% | 30 | Backbone-native archetypes |
| SASRec | MovieLens | +17.0% | +26.9% | 30 | Contextual baseline + Lattice |
| LSTM | Amazon Electronics | +10.7% | +17.3% | 30 | Supporting — 5k test rows |
Headline: LSTM +31.7% gated (+58.7% ungated). Transformer +13.3% and SASRec +17.0% use backbone-native archetypes. Amazon +10.7% is supporting cross-domain evidence (30 seeds, 5k test rows). We are not selling peak benchmark mode — we sell an ON/OFF switch that does no harm when off.
Always-on fusion scores higher on pooled benchmarks in our ablation (+58.7% vs +31.7% gated on MovieLens). We do not sell peak benchmark mode. We sell a switch you can audit: off means your backbone; on means full fusion gain on supported rows.
Lattice decides whether an auxiliary scoring path gets composed with your backbone — not whether items vanish from the list. Gate OFF: rankings match your backbone exactly. Gate ON: same as always-on fusion on that session.
Mock rankings for education only — composition policy (OFF ≡ backbone, ON ≡ fusion), not item filtering. Does not expose production confidence formulas or training pipelines.
Pilots focus on three things: coverage when ON, lift when ON, and zero harm when OFF. Hosted API access comes after a pilot validates — not self-serve yet.
A Banlys product · Patent pending · RecSys 2026 under review · LorianBannis@banlys.com