AI Readiness: AI That Delivers - Because the Foundation Is Right
Many companies experiment with AI. Few scale successfully. The difference lies not in the technology, but in the quality of the data and the reliability of the solutions. We support you on the journey from initial use cases to productive AI applications.
Your Path to a Data-Driven Organization
BIG.Cube supports companies through three consecutive steps. Stage 3 is the goal—but it can only be achieved on a stable foundation.
Stage 1
Data Platform
Reliable, integrated data foundation as the basis for analytics and AI.
Stage 2
Analytics Strategy
Reports, dashboards, and self-service for all business areas. From embedded analytics for operational reporting and integrated planning to usage in AI applications.
Stage 3
AI Readiness & Reliable AI
Reliable AI applications based on high-quality data.
Prerequisites for Stage 3:
Stage 1: Data That AI Can Trust
AI models are only as good as the data they are trained on. Without an integrated, quality-assured data foundation, even the most advanced models produce flawed results.
Stage 2: Analytics as the Bridge to AI
Companies that already use data for reporting and planning have a deeper understanding of their data and can more effectively identify and validate AI use cases.
AI that Rruly Works in a Business Context
AI experiments are easy. Productive AI is hard. Reliable AI means results that are transparent, consistent, and reliable – even when input data is complex and users are not data scientists.
Explainable AI
AI recommendations must be explainable for decision-makers, auditors, and regulatory requirements. We build solutions with transparency –by-Design.
Data Quality as an Ongoing Priority
Reliable AI requires continuous data quality monitoring. One-time, well-built pipelines are not enough. . We establish continuous quality assurance. In addition to the capabilities of the tools used, we leverage our own product, Q-THOR, in our projects..
From Prototype to Production
The transition from proof of concept to productive deployment often fails due to infrastructure and governance.. We support this step with a clear architecture.
Business-Relevant Use Cases - Not Lab Experiments
The value of AI does not come from technology alone, but from the right combination of data, processes, and use cases. We leverage your data from Stage 1 and the analytical maturity from Stage 2 to apply AI where it creates the greatest impact.
- AI-Supported Development
- Forecasting & Predictive Analytics
- Anomaly Detection & Alerting
- AI-Driven Process Automation
Shorter time-to-value through AI-supported development processes—implementations delivered in weeks instead of months.
Sales, demand, and risk forecasts based on historical SAP data—directly integrated into existing planning processes.
Automatic detection of anomalies in financial data, supply chains, or production processes with explainable root causes, not just alerts.
Automation of repetitive decision-making processes—from invoice verification to inventory optimization—based on reliable data and clear rules.
More Than Experiments: AI That Delivers
We turn your use cases into production-ready solutions.
BIG.Cube GmbH
Seitzstraße 8a // TH1
80538 Munich
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From AI Strategy to Production-Ready Solutions
We support you from the first use case to scalable AI applications – with a focus on reliability, transparency, and real business value.
AI Readiness Assessment
AI Readiness Assessment
Use Case Identification & Prioritization
Use Case Identification & Prioritization
Implementation & Integration
Implementation & Integration
Governance & Monitoring for AI Applications
Governance & Monitoring für AI-Anwendungen
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Ready for the Next Step?
In a free initial consultation, we assess your AI readiness and identify which use cases are realistic and valuable for your business today.
BIG.Cube GmbH
Seitzstraße 8a // TH1
80538 Munich