synvert MLOps Framework

In today’s world, every organization strives to leverage their data with ML and AI tools. They develop POC models from intriguing ideas and use cases. However, these POCs often fail to progress to a production-ready state. Similar to conventional software engineering, there is a need for an ML framework to enable these ML use cases to be deployed in production. We offer a generic and reusable MLOps platform that combines the best practices of software engineering and machine learning. Our solution, built using MLflow and AzureML, offers a CI/CD framework covering all aspects of the ML model lifecycle, from data cleansing to model deployment. To build future-proof models, we have incorporated advanced monitoring, including data drifts and error analysis, to keep our models updated over time. Our object-oriented approach ensures a reusable, modular, and scalable framework that can be easily adapted to the changing needs of our customers. We have also incorporated AutoML in our framework, enabling customers without expertise in data science to effortlessly deploy state-of-the-art ML models onto their datasets.

We offer quick onboarding to our interested customers, consisting of three phases:

Brainstorming (1 Week): We organize several meetings with stakeholders to understand business needs and the existing cloud platform.

Build (3 Weeks): We incorporate our ML framework into your Azure infrastructure. We have readily developed assets that just need to be configured according to your operational and infrastructure system. We integrate your models with our framework, ensuring a seamless and production-ready deployment.

Ops (On Demand): We monitor and maintain your MLOps platform.

Our solution ensures a sustainable and evolving ML Platform to deliver continuous insights and value from your data.