ML modernisation
Reach a new level of efficiency and productivity
Streamline and automate model development with our expert data engineering and machine learning capabilities.

Can your organisation build and iterate on ML models with confidence?
We have a proven track record of helping organisations reach a new level of efficiency and productivity by integrating MLOps into their machine learning lifecycle. We can help you:
- Migrate existing machine learning pipelines to a fully managed, high availability service.
- Speed up model development, and build and deploy repeatable machine learning pipelines.
- Manage different stages of the machine learning pipeline such as data labelling, feature engineering, model creation and deployment.
- Develop human-in-the loop pipelines for more efficient data collection and labelling.
- Monitor models in production, detect performance degradation or data and model drift, and automate the model retraining process.
DiUS can help you automate and accelerate your ML lifecycle so your teams can focus more on delivering business value rather than managing infrastructure and platforms.
We start with an initial assessment of your existing data engineering, model and deployment pipelines, then assess your level of maturity to develop a strategy for migration or modernisation.
We might start with the migration of a model or models from on-premise, other cloud vendors, or EC2 instances onto Amazon SageMaker to take advantage of features such as automated pipelines or introduce some specific features, such as ML lineage tracking if reproducibility, governance or auditing is important.
In any case, our initial assessment and initial steps will set the foundation for better practices and modernisation to increase productivity, shorten the path to production and provide ML teams with the ability to collaborate more effectively and iterate quickly. And we’ll do all of this by working side-by-side with your teams to provide capability uplift so you can continue on your own with confidence.
Start leveraging the potential of ML with MLOps
Book in a complimentary discovery session to discuss the challenges with your ML lifecycle, and learn how DiUS can help you achieve them.
We can provide options for nearly any need, timeline, or budget.
Complete the form below to book your discovery session with DiUS.
About DiUS
DiUS helps organisations use emerging technology to solve difficult problems, get new ideas to market or disrupt traditional business models.
We have been an AWS Advanced Consulting Partner since 2012 and were the first to attain the AWS ML Competency in ANZ and the AWS Applied AI Competency in APJ.
We build, productionise and scale ML-powered solutions that can be deployed to the web/mobile or IoT devices such as wearables, drones and monitoring equipment. We drive innovation and impact through leveraging ML-as-a-Service and MLOps, as well as building custom state-of-the-art machine learning models.

