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Small, reproducible Python demos illustrating how scientific and data workflows support business decisions. Each example links to source under demos/ in the GitHub repository.

Demand and uncertainty

Forecast monthly demand with prediction intervals to frame inventory risk.

A/B testing decisions

Turn experiment results into effect sizes, confidence intervals, and a plain-language decision.

Segmentation

Cluster customers or products and summarize each segment with interpretable profiles.

Margin what-if

Explore price and cost sensitivity with simple elasticity-style scenarios.

Multimodal support signals

Fuse text, product/channel, and attachment signals; cluster and track weekly mix.

Repeatable weekly report

Generate templated HTML from CSVs with Python and Jinja2; English and Spanish UI strings.

All demos share dependencies listed in demos/requirements.txt. Run instructions are in demos/README.md and each demo folder.