aiqu.systems

Service · Anticipate

Forecasting that tells your team what to order, stock and move next.

We build demand, inventory, lead-time and fleet forecasts on your own history in SAP, POS and spreadsheets, then push the result into the tools your planners already use.

  • Demand forecasting
  • Anomaly alerts
  • SAP / ERP
Built onYour data

Sales, stock, supplier and fleet history you already hold, cleaned and consolidated first.

What we build

What we forecast

Forecasts are only useful if someone acts on them, so each one ends in a reorder point, a staffing plan or an alert.

Demand

SKU and outlet demand

Daily or weekly demand per product and location, including promotions, Ramadan and holiday peaks.

Stock

Reorder points and safety stock

Recommended order quantities that balance stock-outs against cash tied up in inventory.

Supply

Supplier lead times

Predicts late deliveries from supplier history, so planners act before the shortage.

Materials

Material consumption

Links planned progress to material usage and flags leakage on project sites.

Fleet

Fleet demand and rebalancing

Forecasts where vehicles will be needed and when to move them.

Alerts

Anomaly detection

Flags unusual sales, usage or stock movements the day they happen.

Process

How an engagement runs

  1. Discovery

    We map the decisions forecasts should drive and the data behind them.

  2. Data foundation

    History from ERP, POS and spreadsheets is cleaned and consolidated.

  3. Model and test

    We back-test against the last 6–12 months so you see accuracy before go-live.

  4. Operate

    Forecasts land in your planning tools, with retraining as patterns change.

Why forecasting starts with data

Most forecasting projects fail on messy data, not on the model. That is why many engagements start with our Data Integration service and a single source of truth.

Related work

Case studies from our founders' work at previous companies, before AIQU Systems.

Frequently asked questions

How much history do we need for demand forecasting?

Ideally 12–24 months of sales or usage data per product and location. Less can work for fast-moving items; we check during discovery.

Does it work with SAP and Excel?

Yes. We connect to SAP and other ERPs, POS systems and shared spreadsheets, and can write results back to them.

How do we know the forecast is good?

We back-test on your own past data and agree an accuracy measure, such as forecast error by SKU, before go-live.

Can it handle Ramadan and holiday peaks?

Yes. Calendar events, promotions and local holidays are built into the model as explicit features.

Find out what your cameras are missing.

Start with a Vision Assessment: 2 days of your existing CCTV footage, a loss report in rupiah within 10 working days, and the Rp 25.000.000 fee credited in full toward a pilot.