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Optimisation & Scaling
The ModelOps/MLOps
In the boutique consultancy world, clarity is currency. This offering bridges the gap between technical rigor and business value, delivering standardized MLOps capabilities that reduce friction, mitigate risk, and enable scale across your Azure AI environment.
Optimisation & Scaling
ModelOps/MLOps
Complete MLOps reference architecture and governance framework delivering standardized model lifecycle management, CI/CD pipelines, and operational excellence.
Core Outputs
MLOps Reference Architecture
Infrastructure-as-Code Templates
Standardized Model Lead Templates
Model Governance Framework
Process
12 Weeks
Outcomes
Reduced Friction, Risk & Scale
MLOps Maturity Operationalized
Your Journey With Orion
Where This Product Fits In Your Transformation
The Approach
Comprehensive MLOps Implementation
We deliver a complete MLOps foundation with reference architecture, infrastructure automation, standardized templates, and governance frameworks to operationalize your model lifecycle.
Foundation & Architecture
We establish the foundational MLOps architecture and delivery framework.
- MLOps Reference Architecture design and documentation
- Azure environment setup and security hardening
- Stakeholder interviews and requirements gathering
Pipeline Integration & Automation
We build and integrate CI/CD pipelines with automated testing and validation.
- Infrastructure-as-Code templates and deployment automation
- CI/CD pipeline development for priority models
- Automated testing and validation gates establishment
Governance & Handover
We establish governance frameworks and enable your team for long-term success.
- Model Governance Framework implementation
- Model monitoring dashboards and alerting setup
- Team upskilling and knowledge transfer
What You Get
Complete MLOps Capabilities
A comprehensive MLOps foundation with reference architecture, standardized templates, infrastructure automation, and governance frameworks for operational excellence.
01
MLOps Reference Architecture
Comprehensive reference architecture providing standardized patterns, best practices, and architectural guidance for building robust MLOps capabilities on Azure Machine Learning.
02
Infrastructure-as-Code Templates
Ready-to-deploy IaC templates for Azure resources, enabling consistent, repeatable infrastructure provisioning and reducing manual configuration errors.
03
Standardized Model Lead Templates
Pre-configured model lead templates providing standardized patterns for model development, training, validation, and deployment workflows.
04
Model Governance Framework
Complete governance framework with policies, procedures, and automated controls for model lifecycle management, monitoring, and compliance.
Benefits
Why Choose The ModelOps/MLOps Offering?
Standardised MLOps capabilities that reduce friction in model deployment, mitigate operational risks, and enable sustainable scale across your organisation.
Reduced Friction
Streamlined model deployment processes through standardized templates and automated pipelines reduce time-to-production and eliminate manual errors.
Risk Mitigation
Automated testing, validation gates, and governance frameworks ensure model quality and compliance, reducing operational and regulatory risks.
Scale
Standardized patterns and infrastructure automation enable consistent, repeatable model deployments at scale across teams and use cases.
Operational Excellence
Complete MLOps foundation with monitoring, governance, and team enablement ensures sustainable operational excellence and continuous improvement.
Engagement Structure
Twelve Weeks To Operationalized MLOps
A structured engagement taking you from foundation setup through pipeline integration to complete governance and team enablement.
1
Week 1 • Foundation
Stakeholder Engagement & Environment Setup
Conduct stakeholder interviews to understand requirements and priorities. Set up Azure environment with security hardening. Deliver "The Download" foundational assets including reference architecture documentation.
2-8
Weeks 2-8 • Pipeline Integration
MLOps Pipeline Development & Integration
Integrate data sources with Azure Machine Learning. Build CI/CD pipelines for the first priority model. Establish automated testing and validation gates. Deploy Infrastructure-as-Code templates and standardized model lead templates.
9-12
Weeks 9-12 • Governance & Handover
Governance Framework & Team Enablement
Set up dashboards for model monitoring and alerting. Implement Model Governance Framework with policies and controls. Upskill the client's internal team through training and knowledge transfer. Deliver final "Momentum" report and long-term scaling roadmap.
Value & Confidence
Measurable MLOps Outcomes
The ModelOps/MLOps offering delivers tangible improvements to deployment speed, operational risk, and organizational scalability with clear business value.
0%
Faster Deployment
Reduced time-to-production through standardized templates and automation.
0%
Risk Reduction
Automated testing and governance frameworks ensure model quality and compliance.
0x
Scale Capacity
Standardized patterns enable consistent model deployments at scale.
Powered by Microsoft Azure Machine Learning and MLOps best practices.
Powered By
Microsoft MLOps Technology Stack
We leverage Microsoft's enterprise-grade MLOps tools and services to deliver comprehensive model lifecycle management capabilities.
Azure Machine Learning
Azure DevOps
Azure Pipelines
Azure Monitor
Microsoft Purview
Bicep / ARM Templates
Azure Application Insights
Azure Data Factory
Azure Kubernetes Service
Azure Key Vault
Azure Machine Learning
Azure DevOps
Azure Pipelines
Azure Monitor
Microsoft Purview
Bicep / ARM Templates
Azure Application Insights
Azure Data Factory
Azure Kubernetes Service
Azure Key Vault
Let our expert team help you build a complete MLOps foundation with standardized templates, automated pipelines, and governance frameworks. Contact us today to begin your MLOps journey.
Start Your MLOps Journey