Forecasting Intelligence  Lab

Demo

The Interactive Research Lab

A hands-on demonstration of the forecasting and inventory simulation engine.

What the app does

Explore the experiment, don’t just read about it.

  • 01 Run the forecasting and inventory simulation pipeline
  • 02 Select datasets, demand series and forecasting methods
  • 03 Visualise forecasts and compare model accuracy
  • 04 Simulate inventory outcomes under configurable cost scenarios

Run it locally

The interactive lab is a Streamlit application in the repository (app/). It is separate from this presentation website, which is a static front end and does not load the Python research engine. 

cd forecasting_intelligence
# set up the Python environment (3.11) and install requirements
python -m venv .venv
.venv\\Scripts\\activate        # Windows
pip install -r requirements.txt

# launch the interactive lab
streamlit run app/app.py
# open http://localhost:8501

To be updated after deployment. A hosted lab URL will be added when the application is publicly deployed. For now, run it locally with the steps above.