Governance of multi-agent BPM systems: scaling autonomous processes
Balancing AI agent autonomy and compliance requirements in enterprise architecture using BPMN, DMN, and UnityBase platfo...
Artificial intelligence (AI) is a class of technologies using machine learning, natural language processing, computer vision and generative models to automate analytical and operational tasks.
Balancing AI agent autonomy and compliance requirements in enterprise architecture using BPMN, DMN, and UnityBase platfo...
Why connecting AI agents to document management as external services fails, and how the Data as Infrastructure concept h...
Protecting enterprise workflows from excessive AI agency using domain model architectural constraints to turn AI agents ...
Transitioning to autonomous AI agents requires shifting infrastructure focus: from model selection to building FinOps li...
Integrating third-party AI modules into BSS/OSS creates critical "black box" risks. We examine practical tools for isola...
Adapting the NIST AI RMF 1.0 framework for operational technology (OT), where availability and safety outweigh confident...
How to build reliable safeguards when moving from classic OCR to Intelligent Document Processing (IDP), configure hybrid...
Preventing excessive AI agency in corporate processes using BPMN and DMN standards and strict architectural platform-lev...
How to build reliable controls and avoid AI errors during automated data extraction from contracts and invoices in large...
How to prepare corporate data and optimize compute costs to ensure AI implementation does not result in uncontrolled clo...
Transforming ISO/IEC 42001 requirements into engineering controls within the SDLC to ensure automated evidence for succe...
Traditional RBAC cannot mitigate Excessive Agency risks. We explore architectural methods to constrain autonomous AI age...