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: • Deploying quality models into production at high velocity • Identifying the right time to retrain the models • Enabling teams with the right mix of skills and tools to work efficiently • Ensuring that the cost of ML capability is affordable to the business and delivers the right level of ROI.

MLOPs as a discipline addresses these challenges, brining DevOps principals into ML initiatives to help standardize operations and infrastructure, improve efficiencies, repeatability, accelerate time to market at scale. Companies that see machine learning as strategic realise that that they need to develop MLOps capabilities but often don’t have the right skills or sufficient time and resources.

Data Reply developed an MLOps Accelerator working with leading global brands in various industries. The Accelerator leverages IaC framework that automates the creation and configuration of core AWS resources to power an MLOps-enabled platform and adheres to AWS's best practices (AWS WAF ML Lens). The accelerator is based on AWS native services, but can be integrated with your as-is environment.

Benefits achieved with our customers include: • Route to live reduced by at least 30% and can be achieved within 2 weeks • Implementation of overall MLOps capability is accelerated by c. 3 times • Infrastructure costs reduced by 30% • Data Scientists can be onboarded within 2 weeks

The solution has been validated by AWS MLOps Solutions Architects as part of the AWS MLOPs partner enablement programme for selected trusted AI ML partners