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The intelligence layer includes AI decision aids that help you build better plans. They propose — you stay in control and review before committing.

Decision vectors

Solya’s decision layer computes decision vectors: per variant-and-shop scores such as restock urgency, stockout risk, overstock risk, surplus/deficit, transfer urgency, and a recommended discount. These scores drive the recommendations across plan types and the score-driven workflow strategies.

Plan simulation

Simulation runs a plan against the decision layer without persisting anything. You pick an entity grain (brand / product / variant), an action family (restock / rebalance / markdown), a strategy, and optionally a ruleset; Solya returns the items it would add and with what quantities or discounts — along with the decision context and which rules applied. You can then add them all, cherry-pick, or discard.

Sales forecasts

Forecasts predict future sales per variant / size / shop over a horizon, with confidence bounds. They feed risk assessment and stock planning, and are surfaced in analytics and as a chart type on dashboards.

How to use them

1

Review recommendations

Recommended quantities/discounts appear when building plans and in the AI hub.
2

Simulate before committing

Use simulation to preview a strategy’s output on a scope, then accept what you want.
3

Lean on forecasts

Consult forecasts to size restock and pre-season plans.
Recommendations respect your rules: the decision layer reads the org’s ruleset (and margin floors, budgets, etc.) when shaping its proposals. Items added from a recommendation are tagged with their attribution in the activity log.