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AI Solution

Forecasting & Prediction

Know what's coming. Act first. Demand, load, churn and risk. Models that turn your history into decisions you can plan around, with the uncertainty shown.

What it is

Every business already forecasts. Usually it is last year plus a percentage, adjusted by whoever has the most experience in the room. That works until it does not: a promotion, a heatwave, a new competitor, a supply shock. A forecasting system learns those patterns from your history and external signals, and gives you a number with a range around it, at the level you actually plan on.

Prediction is the same idea pointed at events instead of quantities. Which customers will churn, which machines will fail, which projects will run late. The output is a ranked list your team can act on this week.

How we approach it

We start by measuring your current method. Whatever you do today becomes the baseline, and every model we build has to beat it in a backtest on your own data before anyone gets excited. That backtest also tells us where the model is weak, which is usually more useful than where it is strong.

We then build the pipeline around the model: data refresh, feature engineering, retraining on a schedule and monitoring for drift. The forecast is delivered where your planners work, with an honest interval rather than a false precision. When the range is wide, that is information too.

What you get

A validated model with a written backtest report in your metrics. A production pipeline that refreshes, retrains and monitors itself. Integration into the tools your planners use. And a short guide, written for the people acting on the numbers, explaining what the forecast is, what it is not, and when to override it.

What we deliver

What you get.

  • Baseline and backtests against the method you use today
  • A forecasting pipeline with scheduled retraining
  • Prediction intervals, not just single numbers
  • Integration with your planning tools, ERP or dashboards
  • Drift monitoring that tells you when the world has changed
  • A plain-language guide for the people who act on the numbers

Use cases

Where it applies.

Demand forecasting

Sales, orders and stock at the level you plan on, whether that is per product, per store or per week.

Energy and water load

Consumption forecasts per zone or substation that account for weather, season and holidays.

Churn and retention

Which customers are likely to leave next month, and what is driving it.

Pricing and inventory

Price elasticity and reorder points that respond to the forecast instead of last year's spreadsheet.

Maintenance and failures

When equipment is likely to fail, from sensor and maintenance history, so crews go before it breaks.

Effort and delay prediction

How long projects and tickets will really take, based on how similar ones went.

Selected work

Projects in this area.

Outcomes are described the way the client experienced them. Ask us for the numbers on a call.

EYDAP

Problem

The Athens water utility needed demand forecasts across its network to support operational planning.

Outcome

Forecasting models feeding planning, built and validated on the utility's own historical data.

Numerai

Problem

Predicting financial signals on obfuscated hedge-fund data, where noise dominates and overfitting is the default failure.

Outcome

Models that competed on live market data, developed as the founder's MSc thesis and refined over successive rounds.

Project Pro

Problem

Project effort and delay were estimated by gut feeling, and portfolio planning suffered for it.

Outcome

Prediction models for effort and delay risk that fed portfolio planning decisions.

Questions

Things people ask us.

How much history do we need?

Two years is comfortable for seasonal businesses, but we have built useful models on less. The first thing we do is check what your data can support and tell you honestly.

How accurate will it be?

We backtest against the method you use today and report the improvement in your own units, such as fewer stock-outs or lower forecast error per store. If we cannot beat your baseline, you find out in week two, not month three.

Will it keep working next year?

Models drift as the world changes. We ship scheduled retraining and monitoring that flags when accuracy drops, so the system stays honest.

How do the numbers reach the people who use them?

However they already work. An API, a nightly export into your ERP, a dashboard, or a spreadsheet if that is where planning really happens.

Want Forecasting & Prediction for your business?

Tell us about the problem. We'll tell you if AI is the right tool and what it would take.