Four phases. Three architectural layers. Nine governance domains. A systematic approach to SAP on Azure governance that produces measurable, board-reportable outcomes.
Three-layer architecture diagram showing Execution Plane, Governance Plane, and Semantic Integrity Layer with workload mapping.
Pritesh Delivery — PendingEvery Skynome engagement follows a four-phase methodology designed to move organizations from ungoverned to governed — with measurable progress at every stage.
Every engagement starts with a GRS assessment. We score your SAP on Azure estate across 9 governance domains, identify gaps, quantify risk exposure, and establish your governance baseline. No assumptions — just data.
GRS Score, Risk Heat Map, Board Summary
Based on your GRS scores, we architect a prioritized remediation roadmap — 30/60/90-day milestones, resource requirements, cost estimates, and dependency mapping. The roadmap is actionable, not theoretical.
90-Day Roadmap, Cost Impact Model, Architecture Blueprint
We implement governance controls across your SAP on Azure estate — Azure Policy definitions, integration SLOs, AI governance frameworks, extraction compliance monitoring, and FinOps guardrails. Every control is measurable.
Policy-as-Code, SLO Dashboards, Compliance Documentation
Governance isn't a one-time event. We establish ongoing GRS monitoring, quarterly governance reviews, anomaly detection, and continuous improvement cycles. Your governance posture improves over time, not just at deployment.
Quarterly GRS Reviews, Anomaly Alerts, Board Reports
Visual journey diagram showing the Assess → Plan → Govern → Optimize progression with milestone markers and GRS score evolution.
Pritesh Delivery — PendingThe Skynome v3.0 architecture organizes governance across three distinct layers — each with its own scope, controls, and measurable outcomes.
The infrastructure and workload layer — Azure landing zones, SAP compute, integration runtimes, data extraction pipelines, and AI services. This is where work happens.
The policy and enforcement layer — Azure Policy, RBAC, SLO definitions, cost governance rules, and compliance monitoring. This is where control is enforced.
The intelligence layer — AI governance policies, model selection criteria, data sovereignty rules, and cross-platform policy orchestration. This is where meaning is protected.
We don't staff projects — we govern them. Skynome provides the governance framework, not the implementation army.
Our deliverables are measurable (GRS scores), not subjective (consultant opinions).
We leave behind governance infrastructure, not PowerPoint decks.
We're platform-agnostic within the SAP + Azure ecosystem — not selling you another tool.
Governance spans AI, integration, and data — not just one workload domain.
The GRS framework works with your existing tooling, not against it.
We bring cross-industry pattern recognition that internal teams can't develop in isolation.
The GRS provides a standardized benchmark — not an internal team's self-assessment.
We accelerate governance maturity in weeks, not quarters.
The Skynome Whitepaper details the full methodology, architecture, and governance framework. Gated download — coming in Thread 5.