Inventory is a capital allocation decision disguised as a planning output. A supply chain planning system that surfaces every one, scores it against the cash, margin, and service it moved, and owns the baseline that doesn't need your judgment.
Every planning cycle, your team makes thousands of override decisions. Some create value. Some destroy it. The system that captures them does not score them against outcomes. Which means the cost of override is a line item nobody has ever calculated.
of planning overrides destroy value versus baseline. Your system cannot tell you which half.
Measured across scoped deploymentsFor one consumer manufacturer, every 1% of forecast accuracy improvement equated to this much working capital exposure.
Anonymized customer outcomeof last cycle's validated judgment carried forward into next cycle's baseline. Every cycle starts from zero.
Industry pattern across major planning systems"[Placeholder: Executive testimonial. CFO-level quote referencing specific measured outcomes from a scoped deployment. Override rates reduced, decision coverage expanded, capacity gains quantified. Bounded language. Title plus company size required.]"
These are not products. They are diagnostic engagements. Each one answers a question your leadership team is already asking, using your data, in days. The analyses stand on their own whether or not you ever deploy Daybreak.
Every override from the last 6 to 12 months, broken into value-created and value-destroyed. Formatted as a financial statement.
Side-by-side economics of both paths, using your numbers. If hiring wins, we say so.
A dollar number on planning judgment risk that is not on your risk register.
Or skip straight to a conversation.
Talk to our founding teamDaybreak does not just improve the math. It changes who owns the decision, how it is measured, and whether the system learns from it. Agents own baseline decisions under explicit governance. Your team governs the exceptions that matter. Planning productivity scales with decisions, not headcount.
Every override scored against the outcome it changed. Value-positive interventions reinforced. Value-negative interventions flagged and priced. Forecast accuracy improves 7-9% in scoped deployments because the system stops repeating the decisions that do not work.
Agents handle the volume. Your team handles the judgment. In measured deployments, 70%+ of the portfolio runs under governance without human intervention. Coverage expands without adding planners.
Judgment compounds instead of resetting every cycle. Working capital, margin, and service measured against your pre-deployment baselines. Not a projection. Measured results in governed enterprise deployments.
Baseline decisions owned. Exceptions supervised. Every override measured against outcomes.
Dawn makes governed decisions across thousands of SKUs each cycle, each with full decision provenance. The cost per decision falls as coverage expands.
When risk thresholds are crossed or governance boundaries are reached, items surface for planner judgment, protecting margin where governed autonomy reaches its scope limit.
Planners focus where their judgment has the highest override value-add, on the critical exceptions, not on every SKU.
When actuals arrive, every decision is measured against results. Override effectiveness becomes visible, and value leakage from poor interventions becomes quantifiable on the P&L.
Baseline decisions owned. Exceptions supervised. Every override measured against outcomes.
Dawn makes governed decisions across thousands of SKUs each cycle, each with full decision provenance. The cost per decision falls as coverage expands.
When risk thresholds are crossed or governance boundaries are reached, items surface for planner judgment, protecting margin where governed autonomy reaches its scope limit.
Planners focus where their judgment has the highest override value-add, on the critical exceptions, not on every SKU.
When actuals arrive, every decision is measured against results. Override effectiveness becomes visible, and value leakage from poor interventions becomes quantifiable on the P&L.
Before: systems produce numbers, humans do the work. After: agents do the work, humans govern. The thesis is bigger than one vendor. We wrote the operating model.
Read the AI labor model
Three diagnostics. Each answers a different question your leadership team is already asking. The analyses stand on their own whether or not you ever deploy Daybreak.