Data Science & Artificial Intelligence

Data science extracts patterns, deviations and relationships from collected data. Business intelligence and decision support bind those outputs to sales, finance, operations or customer decisions.

Typical work includes reporting and dashboards, forecasting, segmentation, anomaly detection and scenario analysis. Which input yields which output from a model or analysis should be written and repeatable.

Reliable analytics follows source and quality definition first, then the model or indicator, then the operating screen. The output is an updatable decision-support arrangement.

AEON also builds data platforms, reporting, forecasting and decision support for non-industrial firms. Data warehouse / lakehouse, ETL, self-service BI, scoring models and operational monitoring are part of this service.

We use the same engineering language in finance, retail, logistics, healthcare or services: data quality, model validation, acceptance criteria and documentation. A production shop floor is not required.

Delivery includes a data dictionary, ETL / pipeline definition, dashboard set, model card (input–output–validation), acceptance scenarios and an operations guide. User training and first-period monitoring support can be included.

We can start from your existing Excel or finance/CRM sources and move to a warehouse and automated refresh as you grow. Visible reports first, then forecast or score — the sequence is written together.

At AEON the data and model layer follows field measurement. Signal and record definitions are installed first; anomaly detection, optimisation or decision support feed from that record. Model outputs are delivered with a verification period and acceptance criteria.

Linked solutions include process optimisation, planning support, asset health, training-simulation scoring and EnPI/M&V. The output is an auditable record produced from measured inputs.