Proof

The numbers that matter.

We ran it end to end on a representative demonstration portfolio: 18,000 finished-goods SKUs across 7 families, plus 1,201 raw materials. And no, you will not find a single "up to" on this page.

On a representative portfolio

Honest accuracy, real cash.

A quick word on how to read these. Each number carries the context that makes it honest: the portfolio it ran on, the period, the SKU count, and what it was measured against. That is deliberate. In a market full of “up to” claims, the figure that means something is the one you can trace, then reproduce on your own data.

4.1%
portfolio wMAPE (median 8.8% per SKU)
How measured: weighted across the portfolio, over the demonstration period against a recent baseline; the per-SKU median is shown separately because aggregation differs.
99.0%
modelled cycle service level at the optimal policy
How measured: simulated at the optimal policy; a cycle service level (no-stockout probability per cycle), not a fill rate.
$46.7M
working-capital opportunity, modelled (−66.9% vs today)
How measured: modelled as the reduction from the current inventory baseline to the optimal policy, valued at cost, holding service at target.
$1.58M
value at risk, flagged pre-obsolescence (2,784 SKUs)
How measured: inventory value on SKUs trending toward write-off, flagged early; stock at risk, not a booked loss.
$4.8M
inventory value on SKUs below reorder point (5,926 SKUs)
How measured: the inventory value tied to the affected SKUs, not a loss in itself.
1.2M
calculations across 18,000 SKUs + 1,201 raw materials

Representative demonstration dataset: 18,000 SKUs, 7 families, 19,201 references total; not a client portfolio. Results vary by product mix, data quality and current policy, and are validated on your own data during the demonstration.

Book a 45-min demo
45 minutes. Your data. No slides.
ManufacturingDistributionHealthcareAerospaceEnergyFood & beverageUtilities
Selected work

Engagements across Canada, the US and Morocco.

Distribution · Canada

Min/max to deterministic

A distributor ran ERP min/max on thousands of SKUs and could not say why any number was set. We replaced it with deterministic policies and freed working capital while holding service.

Food & beverage · Morocco

Perishable right-sizing

A short-shelf-life portfolio was writing off stock every month. Pre-obsolescence detection caught the slow movers early and cut the write-downs.

Manufacturing · multi-site

Service without the cash

Fill rate was stuck, and every attempt to lift it meant more inventory. We raised service across sites with no net inventory increase, by right-sizing each item.

Questions

Everything you are probably wondering.

What exactly does DemandIntel do? +

It forecasts demand and sizes your inventory, sitting on top of your ERP. AI sharpens the forecast; the stock and cash decisions run deterministically, so the same inputs always give the same answer and you can explain any number months later.

Is it AI, or not? +

Both, in the right places. Machine learning makes the forecast sharper, while the inventory and cash decisions stay deterministic. AI improves the number; it never decides it behind a curtain.

Does it replace our ERP? +

No. It sits above SAP, Oracle, Dynamics, NetSuite, Sage or your own system, optimizes monthly, and writes the settings back. Nothing to rip out, no rip-and-replace.

Which systems does it connect to? +

Anything that can export your demand and inventory history. We map it to your ERP once, and from then on it reads your data and writes its recommendations back where your planners already work.

What data do you need to get started? +

Your sales or demand history, your current stock positions, and basic item and lead-time data. If your data is messy, that is normal; tidying it up is part of what we do, not a prerequisite you have to finish first.

How long does it take to deploy? +

The free 45-minute demo runs on your own data in a single sitting. A full on-premise install is measured in weeks, not the multi-quarter projects you may be used to, because there is nothing to rip out.

Where does our data go? +

Nowhere. It runs on-premise, inside your walls, on your schedule. Your data never leaves, and every number stays reproducible and ready for audit.

What about items with little or no history? +

We handle new and slow-moving items explicitly, leaning on the behavior of similar products and your planners' input rather than pretending the history exists. You still see how each of those numbers was built, exactly like the rest.

How accurate is it, really? +

On a representative portfolio it reached 4.1% error across the whole book, with a median of 8.8% per SKU. We do not ask you to take that on faith; we rerun it on your data in the demo, so the accuracy you see is your own.

How fast do we see results? +

You see the opportunity on your own data inside the 45-minute demo. Most clients feel it in the stock and the cash within three to six months of going live.

Do you work with mid-sized businesses? +

Yes. It fits focused teams from about 5,000 SKUs up to large groups, across manufacturing, distribution, healthcare, energy and food.

What makes Audacity different? +

Twenty years in the weeds, plus a method you can actually audit. We show the math instead of a black box, and we tie our engagement to results we agree up front; built by planners, for planners.

What happens in the free 45-minute demo? +

We run DemandIntel on your own data and walk through the forecast, the cash it would free and the risks it flags. It is a technical, strategic conversation, and nobody will push you to buy.

How is DemandIntel priced? +

Each engagement combines a software licence with a short consulting phase to put it in place and train your team. We scope the figure to your size and situation after the demo, so you get a number tied to your own operation rather than a list price; the demo itself is free.

How is our data kept secure? +

DemandIntel runs on-premise, inside your own environment, so your demand history, stock and costs never leave your walls; there is no cloud in the loop. Access follows your own controls, and in the free demo your export is used only to run that session and is not retained.

Who supports it after go-live, and how are updates handled? +

We support the deployment and your planners directly. New versions are installed on your schedule, in your environment, never pushed silently; and because every number is reproducible, an upgrade never quietly changes a figure you cannot trace.

What happens after the first engagement? +

What we build stays with you; the model and its settings live in your environment. If you continue, it is on a renewable licence, with your data and configuration yours to keep. No lock-in that holds your numbers hostage.

How do we get started? +

Book the free 45-minute demo and send us a data export when you are ready. That is the whole first step; everything else follows from what we find together.

Value in an hour, not a year

See it on your own data in 45 minutes.

Picture your next S&OP meeting: one number on screen that nobody argues with. See it free, on your own data, in 45 minutes; and if it does not hold up, we part as friends.