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MLOPS SOLUTION

MLOps Maturity Scan

Evaluate and elevate your team's MLOps capabilities.

CONTACT OUR TEAM

Our MLOps Maturity Scan evaluates your team’s current maturity level and identifies
key areas for improvement.

Our MLOps Maturity Scan evaluates your team’s current maturity level and identifies key areas for improvement.

How does it work?

It begins with an intensive, face-to-face workshop, and within just 2 weeks, we’ll deliver a comprehensive MLOps maturity assessment of your team dynamics, tools, and processes, along with actionable insights.

Sam Landuydt
Area Architect at DPG Media
“The Superlinear MLOps Maturity Scan provided us with a new level of insight. We were seeking a second opinion on our AI and MLOps practices, aiming to uncover the hidden gaps and overlooked aspects in our way of working. The detailed analysis exceeded our expectations, encompassing not just MLOps but also development best practices. It was like getting a bird's-eye view of how to tackle our challenges in AI deployment and regular DevOps. This has been instrumental in helping us streamline our processes across DPG Media.”
Pieter Van Bouwel
Team Lead Data Science at Port of Antwerp-Bruges
“The Superlinear MLOps Maturity Scan revolutionized our approach to deploying AI solutions at the Port of Antwerp-Bruges. We were able to start a journey towards smooth collaboration between data scientists and developers. The approach focused on five key dimensions, namely monitoring, rules, maintenance, team and finally the core solution, enabling us to incorporate AI into our operations both efficiently and effectively. This standardized and scalable approach aligns perfectly with our objectives to enhance operational readiness for future AI applications.”
Willem Pieter de Groen
Team Manager Data Science and Insights Translation at Colruyt Group
“The Superlinear MLOps Maturity Scan has been invaluable for us at Colruyt Group. It supported us in streamlining our operational process for deploying AI applications, helping us to align and unify workflows across teams and roles. By providing a scalable and structured method for AI deployment, highlighting gaps and overlooked aspects in our AI and MLOps practices. This has enhanced our organization’s operational readiness for future AI applications. The results have been instrumental in aligning our various teams, ultimately streamlining our AI and MLOps processes.”
Sam Landuydt
Area Architect at DPG Media
“The Superlinear MLOps Maturity Scan provided us with a new level of insight. We were seeking a second opinion on our AI and MLOps practices, aiming to uncover the hidden gaps and overlooked aspects in our way of working. The detailed analysis exceeded our expectations, encompassing not just MLOps but also development best practices. It was like getting a bird's-eye view of how to tackle our challenges in AI deployment and regular DevOps. This has been instrumental in helping us streamline our processes across DPG Media.”
Pieter Van Bouwel
Team Lead Data Science at Port of Antwerp-Bruges
“The Superlinear MLOps Maturity Scan revolutionized our approach to deploying AI solutions at the Port of Antwerp-Bruges. We were able to start a journey towards smooth collaboration between data scientists and developers. The approach focused on five key dimensions, namely monitoring, rules, maintenance, team and finally the core solution, enabling us to incorporate AI into our operations both efficiently and effectively. This standardized and scalable approach aligns perfectly with our objectives to enhance operational readiness for future AI applications.”
Willem Pieter de Groen
Team Manager Data Science and Insights Translation at Colruyt Group
“The Superlinear MLOps Maturity Scan has been invaluable for us at Colruyt Group. It supported us in streamlining our operational process for deploying AI applications, helping us to align and unify workflows across teams and roles. By providing a scalable and structured method for AI deployment, highlighting gaps and overlooked aspects in our AI and MLOps practices. This has enhanced our organization’s operational readiness for future AI applications. The results have been instrumental in aligning our various teams, ultimately streamlining our AI and MLOps processes.”
Sam Landuydt
Area Architect at DPG Media
“The Superlinear MLOps Maturity Scan provided us with a new level of insight. We were seeking a second opinion on our AI and MLOps practices, aiming to uncover the hidden gaps and overlooked aspects in our way of working. The detailed analysis exceeded our expectations, encompassing not just MLOps but also development best practices. It was like getting a bird's-eye view of how to tackle our challenges in AI deployment and regular DevOps. This has been instrumental in helping us streamline our processes across DPG Media.”
Pieter Van Bouwel
Team Lead Data Science at Port of Antwerp-Bruges
“The Superlinear MLOps Maturity Scan revolutionized our approach to deploying AI solutions at the Port of Antwerp-Bruges. We were able to start a journey towards smooth collaboration between data scientists and developers. The approach focused on five key dimensions, namely monitoring, rules, maintenance, team and finally the core solution, enabling us to incorporate AI into our operations both efficiently and effectively. This standardized and scalable approach aligns perfectly with our objectives to enhance operational readiness for future AI applications.”
Willem Pieter de Groen
Team Manager Data Science and Insights Translation at Colruyt Group
“The Superlinear MLOps Maturity Scan has been invaluable for us at Colruyt Group. It supported us in streamlining our operational process for deploying AI applications, helping us to align and unify workflows across teams and roles. By providing a scalable and structured method for AI deployment, highlighting gaps and overlooked aspects in our AI and MLOps practices. This has enhanced our organization’s operational readiness for future AI applications. The results have been instrumental in aligning our various teams, ultimately streamlining our AI and MLOps processes.”
Sam Landuydt
Area Architect at DPG Media
“The Superlinear MLOps Maturity Scan provided us with a new level of insight. We were seeking a second opinion on our AI and MLOps practices, aiming to uncover the hidden gaps and overlooked aspects in our way of working. The detailed analysis exceeded our expectations, encompassing not just MLOps but also development best practices. It was like getting a bird's-eye view of how to tackle our challenges in AI deployment and regular DevOps. This has been instrumental in helping us streamline our processes across DPG Media.”
Pieter Van Bouwel
Team Lead Data Science at Port of Antwerp-Bruges
“The Superlinear MLOps Maturity Scan revolutionized our approach to deploying AI solutions at the Port of Antwerp-Bruges. We were able to start a journey towards smooth collaboration between data scientists and developers. The approach focused on five key dimensions, namely monitoring, rules, maintenance, team and finally the core solution, enabling us to incorporate AI into our operations both efficiently and effectively. This standardized and scalable approach aligns perfectly with our objectives to enhance operational readiness for future AI applications.”
Willem Pieter de Groen
Team Manager Data Science and Insights Translation at Colruyt Group
“The Superlinear MLOps Maturity Scan has been invaluable for us at Colruyt Group. It supported us in streamlining our operational process for deploying AI applications, helping us to align and unify workflows across teams and roles. By providing a scalable and structured method for AI deployment, highlighting gaps and overlooked aspects in our AI and MLOps practices. This has enhanced our organization’s operational readiness for future AI applications. The results have been instrumental in aligning our various teams, ultimately streamlining our AI and MLOps processes.”

Key deliverables of the MLOps Maturity Scan

Key recommendations

Receive 3-5 actionable recommendations tailored to your team’s needs, ensuring concrete next steps to improve your MLOps maturity.

Detailed analysis

Gain insights into your MLOps maturity level with our Capability Maturity Model, identifying where your organization stands today.

Tailored roadmap

Understand the steps required to optimize your MLOps processes, ensuring scalable and reliable AI solutions.

Our mlops framework

MLOps Capability Maturity Model (CMM)

Our MLOps Maturity Scan evaluates your team’s current maturity level and identifies key areas for improvement.

Our proprietary MLOps Capability Maturity Model (CMM) is the cornerstone of all MLOps practices at Superlinear, and the foundation of our workshops.

The Superlinear MLOps CMM Framework consolidates proven principles for building and maintaining AI solutions efficiently and effectively. It enables us to bring best practices to every AI project, ensuring success from the ground up.

Our Machine Learning Engineers and Solution Leads are fully trained in the CMM framework and bring extensive hands-on experience from previous projects.

How does the CMM work?

The 3 questions about your MLOps maturity

The Framework helps answer three critical questions about your MLOps maturity:

Where am I situated today? – Assess your current MLOps maturity level.
Which problems should I solve, and in what order? – Define your Build Order for prioritizing tasks.
Which solutions should I pick for each problem? – Build your ideal MLOps Stack tailored to your needs.

The 3 pillars of MLOps capability

MLOps capabilities are classified under three pillars:

Organization: Team Organization and Development Tooling.
Development: Data Acquisition, Engineering, and Model Development.
Distribution: Model Packaging, Deployment, Serving, and Monitoring.

The 5 maturity levels

For each pillar, we can distinguish five Maturity Levels:

Level 1 – Manual. Model development and deployment is fully manual and has limited documentation or tracking.
Level 2 – Repeatable. Repeatable model development: others can repeat a documented process, which brings improved consistency and quality to the result.
Level 3 – Reproducible. Fully reproducible model development: the result itself is exactly reproducible, which enables both efficient collaboration as well as low-effort maintenance.
Level 4 – Automated. Automated model development and deployment: brings increased efficiency for the team and organization.
Level 5 – Improving. Model development, model performance, and maintenance is optimized to bring continuous improvement.

a man of superlinear working on a computer with the 5 levels of the MLOps maturity assessment

The importance of the CMM Framework

Our MLOps CMM Framework is designed to deliver clarity and efficiency by structuring and summarizing Superlinear’s extensive experience in MLOps.

Targeted Problem-Solving

Predefined, Industry-Standard Stacks

A Dynamic Roadmap

Who benefits from the MLOps Maturity Scan?

Whether you’re struggling with data quality, model deployment, or operational inefficiencies, our MLOps maturity assessment provides a roadmap to accelerate your AI initiatives and achieve scalable, reliable, and high-performing solutions.

Fledgling teams

If you have no AI solutions in production, the workshop serves as a Sound Foundation for your AI journey. We’ll help you start on the right foot and efficiently define a Build Order and Stack for your team.

Teams in transition

If you’re struggling with reliability, reusability, or self-service, we’ll help you pinpoint pain points and make a Course Correction with 3-5 key recommendations.

Established teams

If you’re looking to refine your processes or adapt to organizational changes or new projects, we’ll provide a Second Opinion on your current practices and suggest improvements tailored to your new challenges.