To be considered for the MLOps Platforms category, a product should meet the following criteria: * Platform for Monitoring and Management: The product must provide a comprehensive platform for monitoring and managing machine learning models. This includes features for tracking model versions, monitoring performance metrics, and managing model lifecycles. * Integration into Business Applications: It should allow users to seamlessly integrate machine learning models into various business applications across the company. This integration capability ensures that models can be effectively deployed and utilized within the existing infrastructure. * Health and Performance Tracking: The product must enable users to track the health and performance of deployed machine learning models in real-time. This involves monitoring key indicators such as accuracy, latency, resource utilization, and model drift to ensure optimal performance. * Holistic Management Tool: It should provide a holistic management tool that offers insights into all models deployed across the business. This includes features for model governance, compliance monitoring, and centralized visibility into the entire model ecosystem. Meeting these criteria ensures that the product offers robust capabilities for managing machine learning operations effectively within an organization.
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