Our platform bundles modules that directly integrate into existing workflows: from data preparation to automated reporting. Each module can be introduced individually and scales with your data volume.
Overview of modulesWeekly key figure overviews are created without manual intervention and distributed to the responsible departments. This saves hours in follow-up work and reduces transmission errors.
Reporting effort drops by up to 70 percentProduction utilization, inventory levels, or sales metrics appear on a central screen. The views can be configured by role, so each department only sees the relevant values.
Decisions based on current data instead of weekly reportsMachine learning models identify patterns in historical data and forecast demand, wear, or staffing needs. The predictions are directly incorporated into planning tools.
Early warning of bottlenecks and failuresThe system checks incoming data for completeness, duplicates, and plausibility. Deviations are automatically reported before they affect analyses.
Reliable foundation for every evaluationAlgorithms continuously monitor measurement values and process data. Unusual deviations trigger a notification so your team can react early.
Downtime and quality losses are reducedOur platform connects to ERP, CRM, and IoT solutions via interfaces. The data remains where it is generated – the analysis runs in parallel in the background.
No restructuring of the existing IT landscape requiredTo avoid any misunderstandings: We disclose what our analyses can do, where the limits lie, and how we work with your data.
By AI analysis, we mean the use of machine learning models that are trained on your company data. This includes pattern recognition, forecasting, and anomaly detection. We do not provide generic recommendations, but rather models tailored to your specific processes and data sources.
Our platform integrates common systems such as ERP, CRM, sensor data from production, as well as structured and unstructured databases. We connect your existing infrastructure via standardized interfaces (REST, SQL, CSV). If you use proprietary systems, we will check connectivity in advance.
Data protection is an integral part of our architecture. We work according to the "Privacy by Design" principle: data is pseudonymized or anonymized, access is logged, and processing is documented. On request, we support you with data protection impact assessments and coordination with your data protection officer.
After data integration, we deliver initial dashboards and descriptive analyses within two to four weeks. More complex ML models, such as those for predictive maintenance, require six to twelve weeks depending on data quality and project scope. We define the exact schedule together during the kick-off.
After go-live, we support you with a defined support package. This includes monitoring model quality, regular retraining, and further development of the dashboards. You receive monthly reports on model performance and can activate additional analysis areas as needed.
From the initial data capture to ongoing operation, it usually takes four to six weeks. After that, the platform continuously delivers updated forecasts and recommendations for action.
What our customers report after the first months with the platform
The forecasting models have fundamentally changed our inventory management. We now order precisely based on demand and save on expensive express deliveries.
Lukas Friedl B.Sc. — Head of Supply Chain, Mechanical EngineeringThe dashboard shows me the metrics that really matter every morning. I no longer have to compile reports, and decision-making paths have become significantly shorter.
Sandro Pühringer MBA. — Managing Director, Logistics CompanyThe automated reports completely replace our weekly Excel work. The team uses the time gained for actual analysis instead of data preparation.
Sonja Leitner — Head of Controlling, RetailThe rollout was faster than expected. After three weeks, we had the first models in production, and the results were immediately plausible.
Kevin Urban — IT Project Manager, Energy Supplier