MLOps

The AI ecosystem and pipeline span multiple environments, including data center, cloud, developer notebooks, and platforms. C5i’s MLOps framework is technology-and platform-agnostic, focusing on standardization and scalability across platforms and environments. The end result is that training and deployment processes run smoothly.

C5i’s MLOps framework has 3 core components –

– CI (Continuous Integration) for testing and validating data, schemas, and models.

– CD (Continuous Deployment) for automatically deploying model predictive services and changes within models

– CT (Continuous Training) for automatically retraining and serving the model

C5i’s MLOps solution provides constant monitoring and production diagnostics to improve the performance of your existing models. The use of best practices enables you to track model health, accuracy, and data relevance to explain why your model is degrading or underperforming. C5i’s practices give you constant evaluation and continuous learning to help you avoid surprises in model performance.