AI Services for
Complex Problems
Three specialized AI areas: Quantum-Inspired Optimization, Active Learning, and Meta-Learning. Scientifically sound, practically implemented, measurable results.
Back to HomepageOur Approach
Every AI service is based on scientific research and individually adapted to your business requirements. We combine theoretical excellence with practical implementation.
Analysis & Research
In-depth problem analysis using scientific methods. Identification of the optimal AI technology for your specific challenge based on current research.
Development & Testing
Iterative algorithm development with continuous validation. Comprehensive testing with synthetic and real data for robust, reliable AI systems.
Integration & Support
Seamless integration into existing systems with comprehensive documentation. Long-term support and continuous optimization of your AI solutions.
Our Services
Quantum-Inspired Optimization
Solving complex optimization problems using quantum-inspired algorithms on classical hardware. We implement Quantum Annealing simulations, QAOA approximations, and variational Quantum Eigensolvers for portfolio optimization, molecular simulation, and combinatorial problems.
Portfolio Optimization
Risk-return optimization with quantum algorithms for financial service providers
Molecular Simulation
Quantum chemistry calculations for pharma and materials research
Combinatorial Optimization
Logistics, scheduling, and resource planning using quantum methods
Active Learning Systems
Reduce data labeling costs through intelligent sample selection. Our platforms implement Uncertainty Sampling, Query-by-Committee, and diversity-based selection strategies for maximum learning efficiency with minimal resources.
Uncertainty Sampling
Intelligent selection of the most informative data samples for annotation
Query-by-Committee
Ensemble-based strategies for robust data selection
Multi-Modal Learning
Support for images, text, and time-series data
Meta-Learning Frameworks
Development of AI systems that learn how to learn. We implement MAML, Prototypical Networks, and Neural Architecture Search for rapid adaptation to new tasks with minimal data and Zero-Shot Learning capabilities.
MAML Implementation
Model-Agnostic Meta-Learning for rapid task adaptation
Prototypical Networks
Few-Shot Learning through prototype-based classification
Neural Architecture Search
Automatic optimization of network architectures
Services Comparison
| Feature | Quantum Optimization | Active Learning | Meta-Learning |
|---|---|---|---|
| Project Complexity | |||
| Typical Project Duration | 6-8 Weeks | 4-6 Weeks | 3-5 Weeks |
| Data Requirement | Problem Parameters | Partially Labeled | Task Distribution |
| Main Application | Finance & Logistics | Medicine & QC | E-Commerce & SaaS |
| ROI Timeframe | 3-6 Months | 2-4 Months | 1-3 Months |
Quick Start
Meta-Learning is ideal for initial AI projects with quick results and low effort.
Balanced Solution
Active Learning offers the best balance of efficiency and performance for medium-sized projects.
Maximum Performance
Quantum Optimization for the most complex problems with the highest performance demands.
Technical Standards
Development Standards
Code Quality
All algorithms are developed according to PEP-8 standards, with comprehensive documentation and 90%+ test coverage. Continuous integration and automated code reviews are standard.
Data Pipeline
Robust ETL processes with data validation, versioning, and backup strategies. All pipelines are scalable and can efficiently process large amounts of data.
Performance Monitoring
Continuous monitoring of model performance with automatic alerts for drift or anomalies. Detailed metrics and reporting dashboards.
Security & Compliance
Data Privacy
Encryption of all data in transit and at rest. Anonymization and pseudonymization according to GDPR standards. Local data processing in Switzerland.
Compliance
ISO 27001 Information Security Management and SOC 2 Type II compliance. Regular security audits and penetration tests by external firms.
Backup & Recovery
Automated, daily backups with geo-redundancy. Disaster Recovery Plan with RTO < 4 hours and RPO < 1 hour for critical systems.
Technology Stack
PyTorch, TensorFlow, Scikit-learn, JAX
Pandas, NumPy, Apache Spark, Dask
Docker, Kubernetes, AWS, Azure
Qiskit, Cirq, PennyLane, D-Wave
Which service is right for You?
Unsure which AI service is optimal for your project? We offer a free, no-obligation consultation to find the best solution.