Category: MLOps & Deployment

Model Versioning Strategy

A model versioning strategy is a method for tracking and managing different versions of machine learning models as they are developed, tested, and deployed. It helps teams keep organised records of changes, improvements, or fixes made to each model version. This approach prevents confusion, supports collaboration, and allows teams to revert to previous versions if…

Model Lifecycle Management

Model lifecycle management is the process of overseeing the development, deployment, monitoring, and retirement of machine learning models. It ensures that models are built, tested, deployed, and maintained in a structured way. This approach helps organisations keep their models accurate, reliable, and up-to-date as data or requirements change.

Machine Learning Operations

Machine Learning Operations, often called MLOps, is a set of practices that helps organisations manage machine learning models through their entire lifecycle. This includes building, testing, deploying, monitoring, and updating models so that they work reliably in real-world environments. MLOps brings together data scientists, engineers, and IT professionals to ensure that machine learning projects run…

Service Level Visibility

Service level visibility is the ability to clearly see and understand how well a service is performing against agreed standards or expectations. It involves tracking key indicators such as uptime, response times, and customer satisfaction. With good service level visibility, organisations can quickly spot issues and make informed decisions to maintain or improve service quality.

Pipeline Forecast Accuracy

Pipeline forecast accuracy measures how closely a business’s sales or project pipeline predictions match the actual outcomes. It helps companies understand if their estimates for future sales, revenue, or project completions are reliable. Improving this accuracy allows organisations to plan resources, set realistic targets, and make better decisions.

Hypercare Management

Hypercare management is a focused period of support provided after launching a new system, product, or service. It ensures users have immediate help to resolve any issues and that the transition goes smoothly. This stage typically involves dedicated teams monitoring performance, addressing problems, and collecting feedback to make quick improvements.

Operational Readiness Reviews

Operational Readiness Reviews are formal checks held before launching a new system, product, or process to ensure everything is ready for operation. These reviews look at whether the people, technology, processes, and support structures are in place to handle day-to-day functioning without problems. The aim is to spot and fix issues early, reducing the risk…