MLOps services
How we deliver our end-to-end MLOps services
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Infrastructure analysis and preparation
To kick off, our MLOps experts collaborate closely with your team to holistically analyse your existing infrastructure. We deep-dive into your business requirements and define the specific problems you aim to address with a machine learning model. This approach allows us to build a best-fit roadmap with clear timelines, objectives and KPIs, ensuring your model integrates seamlessly, scales effectively and delivers the desired business value. And, if you need custom ML model development, our data science team will be on hand to support you.
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ML solution architecture design
Our specialist DevOps team will design a robust ML solution architecture that optimises model performance, scalability and maintainability. If you need a custom model, our data scientists and machine learning engineers will perform data preprocessing, cleaning and feature engineering. Then, we’ll develop and train the ML model to handle predictive decision-making in the latter stages of the project.
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Deploying machine learning pipelines in production
Post-architecture, our MLOps specialists will develop pipelines based on your ML models and deploy them into the production environment, ensuring flawless interoperability within your ML systems. We'll oversee the entire deployment process, ensuring no disruption to your operations. Ultimately, we aim for you to leverage machine learning to achieve maximum efficiency and scalability.
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Model monitoring, optimisation and maintenance
Beyond deployment, our MLOps team will provide continuous ML lifecycle management, including model monitoring and optimisation. We’ll track model performance metrics and anomalies and trigger alerts if we find any deviations. Additionally, we can offer continual enhancement of your ML pipelines based on new data, changing trends or evolving business needs. The scope of work may include retraining models and updating them to maintain accuracy and performance over time.
What’s included into our MLOPs process
- Requirement engineering
- ML use cases prioritization
- Data availability check
- Data engineering
- ML model engineering
- Model testing and validation
- ML model deployment
- CI/CD pipelines
- Monitoring and triggering
Why choose ELEKS as your MLOps partner?
