We develop and integrate intelligent solutions that automatically analyze data, identify patterns, and optimize processes. Artificial intelligence and machine learning are applied in a targeted manner to increase efficiency, support decision-making, and create new digital value. The focus lies on practical, operable, and securely integrated solutions.
Machine Learning Models & Predictive Analytics
We develop data-driven models that enable forecasts and detect patterns within complex data structures.
Typical Use Cases
- Prediction of system failures or peak loads
- Forecasting of business metrics
- Anomaly detection in IT operations
- Optimization of resource and capacity planning
Generative AI & Assistance Systems
Modern AI systems support users through automated text generation, analysis, and knowledge creation.
Typical Use Cases
- Intelligent chatbots and virtual assistants
- Automated document summarization
- Support for ticket processing and knowledge management
- Generation of structured content based on existing data
Data Preparation & Feature Engineering
High-quality models require structured and clean data. We prepare data sources and establish reliable training foundations.
Typical Use Cases
- Cleansing and structuring heterogeneous data
- Transformation of raw data into analyzable formats
- Development of standardized data pipelines
- Documentation of training data and data lineage
MLOps & Model Operations
AI models must be operated in a stable, versioned, and monitored manner. We establish processes for training, deployment, and model monitoring.
Typical Use Cases
- Automated training and deployment processes
- Versioning and traceability of models
- Monitoring of model performance
- Continuous improvement through feedback loops
AI Integration into Business Applications
AI functionalities are seamlessly integrated into existing systems and platforms to intelligently enhance processes.
Typical Use Cases
- Enhancement of existing applications with AI capabilities
- Integration into service management or monitoring systems
- Support for data-driven decision-making processes
- Automated analysis and evaluation steps within workflows
Governance, Security & Compliance
AI is implemented responsibly and in compliance with regulations. Transparency, data protection, and traceability are key priorities.
Typical Use Cases
- Documentation of training and decision-making foundations
- Protection of sensitive data in AI processing
- Compliance with regulatory requirements
- Establishment of clear roles and responsibilities
Business Value
The targeted use of AI and machine learning creates intelligent, adaptive systems that increase efficiency, detect risks at an early stage, and sustainably support data-driven decision-making.