Auditing AI solutions in document management: risk management for IDP
How to build reliable controls and avoid AI errors during automated data extraction from contracts and invoices in large enterprises.
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Practical guides to operating models, process automation, transformation governance, management data and controlled AI.
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33 publications
Architecture of multi-agent AI systems in enterprise
Integrating autonomous agents into enterprise ERP and ECM environments requires strict architectural discipline, using DDD and RBAC to mitigate security risks.
Automating business processes with AI agents: maintaining control
Integrating generative AI into corporate processes using BPMN 2.0 and DMN for secure AI agent orchestration and maintaining system control.
Secure process automation using AI agents: risk mitigation architecture
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.
Integrating AI/ML into products: From prototype to production
Transitioning from experimental ML models to robust enterprise systems using AWS Well-Architected Framework, Google SRE, and 12-Factor App principles.
Data governance and data lineage: quality for AI
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.
AI agents in workflow: first-line processing and BPM future
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.
Low-code, RPA, or AI agent: choosing the right approach
Balancing deterministic orchestration and probabilistic AI in enterprise systems to avoid technical debt and critical security risks.
IDP and AI in document management by 2027
Transitioning from traditional ECM to Intelligent Information Management. How IDP and AI technologies automate corporate document processing while maintaining legal validity.
Common ECM migration errors: why IDP and workflows stall
Successful migration to modern intelligent ECM systems requires mandatory design of fallback rules in workflows and the creation of a high-quality training corpus for IDP models.
Integration architecture patterns for AI readiness: from chaos to Data Fabric
AI readiness is defined by architectural data maturity. Transitioning from point-to-point integrations to a managed layer with a unified API contract prevents data processing errors.
Recursive AI self-improvement: preparing businesses for new challenges
The concept of recursive AI self-improvement is transforming process automation. We explore how companies can prepare their data and manage risks.