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Strategic Impact
Our Approach
Environment Strategy and DLP
We defined a clear environment strategy and data loss prevention policies so that where apps and flows run, and what data they can touch, is deliberate rather than accidental. The sprawl that comes with fast adoption was brought under structure.
Access, Ownership, and Lifecycle Standards
Role-based access, ownership standards, and lifecycle rules were established so every app, flow, and agent has a known owner and a defined path from build to retirement. Orphaned, unmanaged assets stopped being the norm.
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ALM and Deployment Discipline
We put application lifecycle management and structured solution deployment in place, with development and production separated. Changes move through a controlled path instead of being edited live in production.
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Agent and AI Governance
Governance was extended specifically to Copilot and AI agents — how they're built, what they can access, and how they're monitored. AI adoption gained the same controls as the rest of the platform rather than running ahead of them.
Center of Excellence Operations
We defined Center of Excellence operating procedures, monitoring, and support processes so governance is something the organization runs day to day, not a one-time cleanup. The framework is designed to hold as adoption keeps growing.
BabyBots Impact Assessment
The Impact
The enterprise can keep scaling automation and AI adoption while materially reducing security, compliance, support, and platform-management risk. Governance shifted from an afterthought applied to sprawl to a standing operating model the organization runs itself. [Add real metric on review, e.g., environments consolidated, or unmanaged assets brought under governance.]
We began with a governance assessment across the platform estate and stakeholders in IT, security, and the business — taking stock of environments, ownership gaps, and where controls were missing. That assessment defined the priorities and the target operating model the governance framework was built to deliver.
- An enterprise Power Platform and AI governance framework
- Environment strategy and DLP policies
- Role-based access and ownership standards
- ALM, solution deployment, and development and production separation
- Agent and AI governance controls
- Center of Excellence operating, monitoring, and support procedures
Project Journey
Project Timeline
Weeks 1–2
Platform Governance — Estate & Risk Assessment (Weeks 1–2)
Assessed the platform estate, environments, ownership gaps, and missing controls with IT, security, and business stakeholders.
Week 3
Platform Governance — Target Operating Model & Policies (Week 3)
Defined the environment strategy, DLP policies, access and ownership standards, and target Center of Excellence operating model.
Weeks 4–5
Platform Governance — ALM & Deployment Framework (Weeks 4–5)
Established ALM, solution deployment, and development and production separation across the platform.
Week 6
Platform Governance — Agent & AI Controls (Week 6)
Extended governance to Copilot and AI agents — build standards, access, and monitoring.
Week 7
Platform Governance — CoE Enablement & Handover (Week 7)
Stood up Center of Excellence operating, monitoring, and support procedures and handed over with documentation and enablement.
Financial Services / Power Platform
Enterprise Power Platform & AI Governance at Scale
We defined Center of Excellence operating procedures, monitoring, and support processes so governance is something the organization runs day to day, not a one-time cleanup. The framework is designed to hold as adoption keeps growing.
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BabyBots is an enterprise technology partner with expertise across process automation, AI systems, data intelligence, and platform architecture.
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