A Leading APAC IT Service Provider Increased ML Model Reusability by 40% Using Open-Source MLOps Workbench

Challenges

The client faced significant challenges in managing their machine learning models:

• Multiple Data Scientists: Models were developed by multiple data scientists using different languages and frameworks.
• Model Management: Needed a platform to manage, re-train, and deploy models in production across various environments.
• Scalability and Real-Time Deployment: Required the ability to scale models for large data sets and run them in real-time.

Solution

Coforge implemented a comprehensive MLOps solution:

Solution Highlights:

• AI Workbench: Built an AI workbench using open-source MLOps tools, enabling seamless model registration, re-training, and deployment.
• Seamless UI: Provided a user-friendly interface for managing models.
• Scalability and Real-Time Operation: Enabled models to scale on large data sets and run in real-time.
• Logging and Access Control: Included features for logging and access control to ensure secure and efficient operations.
• API-Led Development: Implemented a complete API-led development approach for better integration and management.

The Impact

• Improved Collaboration: Enhanced collaboration between data scientists, resulting in a 40% increase in model reusability.
• Reduced Management Time: Decreased model management time from days to hours.
• Scalability and Operations: Improved scalability, better operations handling, and quicker deployment across multiple platforms, enhancing go-to-market (GTM) efficiency.