by Fatima Pervaiz | Jun 12, 2026 | DevOps, MLOps
A fintech startup builds a fraud detection model. It hits 95% accuracy in testing. Investors are impressed. The model goes live. Three months later, fraud slips through undetected. Not because the model was bad because it was never updated. User behaviour changed....
by Fatima Pervaiz | Jun 12, 2026 | MLOps
In a fast-moving AI world, strong MLOps are no longer optional. It is the foundation for building AI that lasts. Uneven model performance, lost experiment history, and failed production deployments — these are the operational failures that derail AI initiatives after...
