DECISIONS & DELIVERY
Practical guides to operating models, process automation, transformation governance, management data and controlled AI.
27 publications
Secure IT/OT convergence requires eliminating direct connections between ERP and SCADA. We analyze the architecture of an industrial demilitarized zone (IDMZ) and asynchronous data exchange.
How to integrate autonomous AI agents into enterprise systems, avoid the risk of Excessive Agency, and maintain full control using BPMN 2.0 orchestration and DMN rules.
Transitioning from experimental ML models to robust enterprise systems using AWS Well-Architected Framework, Google SRE, and 12-Factor App principles.
Transitioning to microservices without considering operational complexity creates technical debt. We examine approaches for building stable enterprise systems.
How to combine the flexibility of custom development with the speed of low-code while maintaining engineering discipline, version control, and robust system architecture.
A practical analysis of architectural patterns for connecting legacy systems to modern ecosystems: how to avoid point-to-point chaos and why RPA is only a temporary solution.
The success of AI initiatives depends on data lineage transparency and Data Governance maturity. Learn how to avoid poor data quality traps and prepare enterprise IT architecture for AI scaling.
How to transition from fragile point-to-point connections to a managed integration layer using API gateways and schema registries to ensure enterprise system stability.
Comparing Kafka and RabbitMQ for building reliable event-driven architectures. Learn how to avoid integration issues and ensure data integrity.
The transition to decentralized architectures and AI integration has revealed a critical bottleneck: the lack of clear data ownership undermines the reliability of enterprise systems.
Comparing architectural approaches: when direct connections become inefficient and how implementing an integration bus helps avoid complexity during scaling.
How to combine the flexibility of AI with the rigid logic of BPMN 2.0 and DMN to automate first-line request processing without security risks or operational chaos.
