Technology & Architecture
Technology that fits your requirements
Development and operation of AI solutions built on modern architectures, aligned with your existing systems.
Flexible architecture models
Depending on your requirements, I work with different architectures, from the cloud to on-premise to hybrid combinations. You get a solution that fits your existing infrastructure and your security requirements.
Cloud
Fast to scale, low entry costs and global availability via AWS, Azure or GCP.
On-premise
Maximum control over data and infrastructure, ideal for sensitive industries and regulated environments.
Hybrid
A flexible combination of cloud and local resources: training in the cloud, inference on site.
Integration into existing systems
AI solutions only create real value once they connect seamlessly to your existing systems and processes. I integrate intelligent components directly into your infrastructure.
APIs & interfaces
REST and GraphQL APIs, webhooks and event-driven architectures for real-time integration.
Databases & SQL
Direct connection to SQL databases, from PostgreSQL to MySQL to SQLite. Your AI solution accesses existing company data in a structured way.
Company documents & file systems
RAG applications with access to internal folder structures, SharePoint, file servers or cloud storage. This turns your documents into a knowledge base.
Applying AI where it matters
Artificial intelligence is used where understanding content or making data-driven decisions is required. Not as an end in itself, but as a precise tool.
Classification & recognition
Automatic categorization of requests, documents or images using trained models.
Extraction & analysis
Structured information extraction from unstructured data such as text, PDFs and images.
Decision support
AI-based recommendations and predictions as the foundation for sound business decisions.
Operations & scaling
Going live is just the beginning. I ensure stable operations, continuous monitoring and scalable infrastructure that grows with your requirements.
Monitoring & logging
Real-time monitoring of model performance, latency and data quality, with alerting.
Scalable infrastructure
Container-based deployment with Docker & Kubernetes, scaling automatically as load increases.
Continuous improvement
MLOps pipelines for automated retraining, A/B testing and incremental model updates.
Security & data protection
Handling data securely is a core part of every solution. From architecture to implementation, data protection and IT security are considered from day one.
Secure processing
Encryption in transit and at rest, secure API authentication and isolated environments.
Access control
Role-based permissions, audit trails and fine-grained access management.
GDPR compliant implementation
Privacy-compliant architecture, data minimization and transparent processing workflows.
Tools
My Tech Stack
Proven technologies from research and industry, combined to fit each project.
AI & ML
Backend
Frontend
DevOps & MLOps
Not sure which architecture is the right one?
I analyze your requirements and walk you through the technical options that fit. No obligation, explained in plain terms.
Discuss your architecture