Mphasis PACE-ML helps enterprises establish MLOps framework and toolchain, enabling data science teams and IT operations to collaborate and manage production pipelines of ML applications and services
Mphasis PACE-ML is the framework and methodology to automate machine learning (ML) pipeline. It leverages workflows, collaboration platforms and tools to streamline management of model selection, versioning, auditability, explainability, re-usability, validation, deployment & monitoring. Built on MLOps principles and leveraging Azure MLOps specific services and open source components, it enables organizations improve quality and reliability of ML solutions in production.
Mphasis offers 6-week PoC implementation led by our AI/ML specialists, and architects. The deliverables of this exercise will be afeature concept MLOps pipeline setup on the Azure cloud etc. which will showcase key elements of versioning, experiment tracking, standardized frameworks, automated ML pipelines, and ML monitoring dashboards
The roadmap for the PoC
Requirements gathering, business and data understanding - 2-3 days
Setup standardized frameworks and checklists for collaboration - 3- 5 days
Versioning and experiment tracking setup – 3 days
Feature Engineering, Model development and evaluation – 4 - 12 days
Automated ML pipeline development - 3 days
Monitoring dashboard - 5 days
Demo and presentation, implementation roadmap for full project- 1 day
Mphasis applies next-generation technology to help enterprises transform businesses globally. Customer centricity is foundational to Mphasis and is reflected in the Mphasis’ Front2Back™ Transformation approach. Front2Back™ uses the exponential power of cloud and cognitive to provide hyper-personalized (C=X2C2TM=1) digital experience to clients and their end customers. Mphasis’ Service Transformation approach helps ‘shrink the core’ through the application of digital technologies across legacy environments within an enterprise. Mphasis’ core reference architectures and tools, speed and innovation with domain expertise and specialization are key to building strong relationships with marquee clients.