Signal-to-Stock Planning Layer
An Agentic OS that turns demand signals into governed buy and replenishment decisions, with planners approving the calls that matter.
Where value leaks today.
Demand planning still runs on a forecast that is stale the day it ships. Statistical baselines live in one tool, promotions in a spreadsheet, supplier lead times in an ERP field nobody trusts, and the reconciliation happens in a planner's head on a Tuesday. Value leaks in the gap between the signal arriving and anyone acting on it — a demand spike shows up in point-of-sale data days before the replenishment order moves, and by then the safety stock is already wrong in both directions at once.
Buying a better forecasting tool does not close that gap. A tool gives you a number; it does not place the order, check it against open POs, flag the parts where confidence is too low to act unattended, or escalate the SKUs where a planner's judgment is genuinely required. The work that actually consumes the planning team — chasing exceptions, re-running scenarios, defending the number in the S&OP meeting — sits in the orchestration layer above the forecast, and that layer is still manual.
What is missing is an operating layer that treats forecasting, inventory positioning, and replenishment as one governed flow: agents that read every relevant signal, propose the decision, and execute the ones inside policy while routing the rest to a human. Kitsune forges that layer around your existing planning stack rather than asking you to rip it out.
One governed flow — agents act, you approve what matters.
Planners stop reconciling forecasts by hand and start approving only the high-stakes buys, while routine replenishment runs governed and on time.
One operating layer — eight governed jobs.
Each is a governed agent inside the same system, sharing context — not eight tools you stitch together.
Signal Fusion Agent
Continuously merges point-of-sale, order book, web, and weather signals into one demand picture. Flags when a signal diverges sharply from the baseline so nothing moves on noise alone.
Baseline Forecast Agent
Maintains statistical and ML forecasts per SKU-location and tracks its own accuracy over time. Surfaces where confidence is too low to act without review.
Inventory Positioning Agent
Sets safety-stock and reorder targets per node against service-level policy. Rebalances positions as lead times and demand shift.
Replenishment Drafting Agent
Translates targets into concrete replenishment and purchase-order proposals. Checks each against open POs and on-hand to avoid double-ordering.
Constraint Check Agent
Validates every proposed order against supplier MOQs, budget, capacity, and shelf-life rules. Blocks or reshapes orders that would violate policy.
Scenario Agent
Runs what-if scenarios on demand, price, and lead-time changes on request. Hands planners a costed comparison rather than a raw model output.
Exception Routing Agent
Separates the decisions inside policy from the ones needing judgment. Routes high-value or low-confidence calls to the right planner with full context.
Accuracy Feedback Agent
Compares forecasts and buy decisions against actuals after the fact. Feeds error patterns back so the next cycle's proposals improve.
Autonomy you can trust — because the control is built in.
The system acts on its own and every action stays legible, bounded, and reversible. You don't choose between speed and control; the control is what makes the speed safe.
Legible
See what was done, what was declined, and exactly what's waiting on you — nothing happens in a black box.
Bounded
Agents act only within the rules you set. Anything material or irreversible stops at a human gate.
Reversible
Every action is logged and undoable. A wrong turn is caught and rolled back, not discovered weeks later.
Owned
One operating system you own — not a swarm of rented agents you have to police. Built, run, accountable.
Planners stop reconciling forecasts by hand and start approving only the high-stakes buys, while routine replenishment runs governed and on time.
What you're actually getting.
Is this a product or a build?
It is a build. Kitsune forges a planning OS around your existing ERP, forecasting, and POS data — owned by you, shaped to your SKUs, network, and service-level policy, not a seat in someone else's tool.
What stays in my control?
Every policy that defines when an agent may act unattended and when it must escalate. High-value or low-confidence buys route to a planner; agents only execute inside the thresholds you set.
How is this different from a forecasting platform?
A platform hands you a number. This layer reads the signals, drafts the order, checks it against constraints, executes the routine calls, and escalates the rest — the orchestration that sits above the forecast.
Will it replace our planners?
No. It removes the manual reconciliation and exception-chasing that fills their week, so their judgment goes to the decisions that genuinely need it — the ones the system deliberately routes to them.
How does it handle new products with no history?
The Baseline Forecast Agent flags thin-history SKUs as low-confidence by default, so they route to a planner with analog comparisons rather than being auto-ordered on a guess.
The same foundry, other domains.
Bring us the bottleneck.
We'll forge the operating layer around your friction — built, owned, and running.