Data Reply MLOps Assessment Framework evaluates Skills, Processes, Tools & Technology deployed in the ML Lifecycle against the AWS MLOps best practices and the MLOPs Reference Architecture.

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As companies gain more experience and business value from AI and ML, the adoption of AI and ML is gathering pace that leads to new challenges.

The key ones are around the ability to deploy quality models into production at high velocity, to identify the right time to retrain the models and to enable teams with the right mix of skills and tools to work efficiently to ensure that the cost of ML capability is affordable to the business and delivers the right level of ROI.

Why MLOps

MLOps Opportunity on AWS

Companies that see machine learning as strategic are developing their MLOps capability - a set principles, practices, processes and technologies to streamline and automate the ML workflow based on DevOps discipline, to enable the use of AI ML at scale.

In Omdia's comparative review of enterprise MLOps platforms, AWS is recognized as “the outright leader”.

Data Reply, works with customers to help them with ML foundations, its productionisation and operationalisation utilising Amazon SageMaker, other Amazon technologies that provide the most comprehensive set of components, tools and automated services for ML.


Benefits of our MLOps Capability Assessment and Advisory

Improved ROI on ML through productivity gains, repeatability & Speed to Business Value

Enhanced Model

Model Governance & Auditability

Improved Collaboration between different teams: Data Science, Data Engineering, Software Engineering, DevOps

Why Data Reply & Our Approach

Data Reply is a premier AWS partner, offering a broad range of advanced analytics, AI ML and data processing services. Data Reply is an AWS Launch Partner in the MLOps competency and part of the AWS ‘Well Architected programme’. Data Reply MLOps Assessment Framework evaluates customers’ Skills, Processes, Tools & Technology deployed in the ML Lifecycle against the AWS MLOps best practices and the MLOPs Reference Architecture.


- Time-Boxed (4 – 5 elapsed weeks), Fixed-Priced Consulting Engagement


- Target MLOps Solution Architecture;
- Documented Recommendations around Target Operation Model based on ‘best practice’ and aligned with business goals and priorities;
- MLOps High level Implementation Roadmap and inputs into a Business Case.

Separately, Data Reply can also assist with the delivery of AI ML projects by augmenting team with the right mix of skills to accelerate time to value and enable knowledge transfer on the project.

Read our Article on MLOps on the AWS Partner Network Blog

MLOps Case Studies Examples

Accelerating the Machine Learning Lifecycle with MLOps

Indicia Worldwide helps global brands improve their customers’ experience using data, machine learning, and AI to fine-tune marketing campaigns, improve retention, and drive new customer growth. It turned to Data Reply to help evolve its data science platform to a more robust, scalable, and efficient solution on AWS. This move cut the time spent building, testing, and deploying new data and machine learning models from months to weeks.


Case Study

Monte Titoli: advanced analytics & Machine Learning on AWS

Storm Reply and Data Reply supported Monte Titoli to define and develop the adoption strategy of Cloud architectures, governance of resources and Machine Learning models.

Machine Learning

Case Study

Machine Learning for long term benefits

In a global enterprise like BMW, translating text is an often necessary, but time consuming and tedious task. Cutting down translation times aids the business in working faster and more efficiently. Reply achieved this for their client providing a low-cost shared service based on AWS for the entire enterprise using BMW’s state-of-the-art neural machine translation models with specific adaption to the automotive domain.

Machine Learning for long term benefits 0

AWS Cloud

Case Study

Getting Cloud and ML into the DNA of Nexi

Data Reply enabled Data Analysis and Machine Learning on AWS Cloud for Nexi, the largest Italian PayTech Company, bringing quantity and quality of data and leveraging Artificial intelligence-based technologies, resulting in major impacts in customer’s capabilities in areas like Fraud, Risk Management, Marketing and Operations, in a safe and compliant way.

Getting Cloud and ML
into the DNA of Nexi 0

machine learning

Case Study

Guarantee the quality of the grinding process

Lavazza chose Amazon Web Services as its cloud platform and Reply, AWS Premier Consulting Partner, to support them in the adoption of machine learning models on AWS. Lavazza worked with Reply to design a product which could fit their needs to predict the results of the tests performed on the production line to guide their operator’s activities.

Data Reply is the Reply Group company that offers excellent services for Big Data and Artificial Intelligence. We operate across most industries and business functions in order to support executive level professionals and Chief Officers to harvest value from data. We build Data Platforms, define and implement ML and AI models in an efficient, replicable and scalable way, by relying upon human resources highly skilled in Big Data Engineering, Data Science and Intelligent Process Automation. Always active on innovations, we are applying Quantum algorithms to support the optimization of processes with high computational needs.