Implementing ECM: Why Big Bang Fails Pilots
Radical transitions to new ECM systems often cause business process disruptions. We examine how phased migration and pilot launches minimize operational risks.
Low-Code
Ideas and experience in communications, technology and customer service.
Modern ECM architecture: balancing dynamic workflows and immutable archives
How to build a corporate ECM architecture that combines flexible approval workflows with ISO 15489-1 requirements and long-term legal validity of electronic signatures.
ECM, DMS, and electronic document management: what enterprises really buy
Why replacing a full ECM system with simple file storage creates critical legal risks when integrating with government services, and how to build a resilient corporate document management architecture.
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.
Architectural defense against AI Prompt Injection and leaks
How to protect corporate LLM systems from Prompt Injection and data leaks at the architectural level in 2025, following NIST AI RMF and OWASP standards.
RPA after ERP: A Bridge or a Digital Patch?
RPA is a useful temporary bridge to legacy systems following an ERP deployment. However, automating Excel-based workflows, email approvals, and fragmented responsibilities often accelerates technical debt rather than resolving it.
AI-Native System Architecture: Ensuring 'Keepalive' Quality and AI Risk Management
AI-native system architecture demands an integrated approach to quality and AI risk management. We examine frameworks, security platforms, and organizational factors.
Enterprise developer: from code to AI system management
AI-native development is transforming the role of the enterprise developer in 2026-2027, shifting focus from writing code to managing AI systems, security, and domain-specific models.
Domain-specific models: when corporate AI needs its own language
Corporate systems require domain-specific language models for security, efficiency, and compliance with unique business processes.
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.
AI and RPA: How data and risks define automation success
Integrating AI into RPA is transforming business processes, but success hinges on data readiness and effective risk management. Prepare your data.
Domain-specific AI models for enterprise applications
Domain-specific AI models are becoming a key tool for modernizing enterprise applications in 2026-2027, overcoming legacy system limitations.