AIDnow – Intelligent Industrial Decision Support
Applied AI for Industrial Analytics & Prediction – From complex industrial data to intelligent decisions and optimized operations.
AIDnow enhances existing IoT and analytics platforms with an AI-powered decision intelligence layer. By combining machine learning, engineering expertise and operational knowledge, AIDnow transforms complex machine, asset and process data into reliable decision support.
Rather than replacing existing platforms, AIDnow builds upon them. It optimizes data acquisition, processing and interpretation while integrating measured data with engineering knowledge and operational experience. The result is transparent, explainable AI that delivers practical value in industrial environments.
Most industrial platforms provide dashboards, KPIs and performance analytics to monitor operations. While these tools help visualize what is happening, they rarely explain why it happens, what will happen next or what actions should be taken.
AIDnow closes this gap by automatically detecting anomalies, diagnosing current asset conditions and predicting future system behavior. Instead of presenting raw data, it transforms complex analytics into clear notifications, prioritized recommendations and actionable insights.
This enables organizations to reduce downtime, optimize maintenance strategies, improve asset availability and make faster, data-driven decisions throughout the entire asset lifecycle.
Anomaly Detection
Identify unusual events and hidden patterns before they become critical.
Condition Monitoring
Understand the current health of your assets and take proactive action.
Predictive Maintenance
Predict future asset conditions instead of reacting to failures.
Demand-driven Integration
Use AIDnow as a retrofit for existing platforms such as SAP or ServiceNow. The modular setup gives you sufficient flexibility. This gives you full control during implementation, in utilization, and for enhancements.
Start with our free demonstration to identify opportunities and risks of your specific use cases in advance.