Enterprise
AI Stack™
Whitepaper & Reference Framework
A comprehensive 6-layer operating model for governing, architecting and deploying enterprise AI systems at scale. Used by engineering leaders, architects and enterprise AI teams globally.
What's Inside
A Reference Framework Built for Enterprise
The Enterprise AI Stack™ Whitepaper is a practitioner-grade reference document — not marketing material. It is designed to be used by CTOs, AI architects, transformation leads and engineering teams designing production AI systems.
- Full 6-layer Enterprise AI Stack™ specification
- Architecture diagrams for each layer
- AI governance operating model
- Deployment lifecycle framework
- AI maturity assessment methodology
- Regulatory alignment mapping (EU AI Act, GDPR)
- Enterprise AI security controls reference
- Implementation roadmap templates
- Model risk management checklist
- Executive summary for board-level briefing
The 6-Layer Framework
Ethics, risk management, regulatory compliance, accountability structures and AI policy frameworks.
Data ingestion, quality, lineage, vector stores, knowledge graphs and enterprise data governance.
Foundation models, fine-tuning, RAG systems, model registry, evaluation and MLOps pipelines.
Agentic AI systems, multi-agent coordination, tool registries, memory and human-in-the-loop.
Enterprise application connectors, APIs, workflow automation and user-facing AI surfaces.
AI monitoring, drift detection, security controls, audit logging and continuous evaluation.
Designed For
Who Uses the Enterprise AI Stack™
CTOs & CIOs
Strategic AI operating model for board-level reporting and enterprise AI governance.
AI Architects
Reference framework for designing production AI systems across the full stack.
Transformation Leads
Implementation roadmap and maturity framework for enterprise AI programmes.
AI Engineers
Technical reference for understanding how production AI layers interconnect.