Censius

Censius is an AI Observability and Model Monitoring Platform that helps teams understand, analyze, and improve the real-world performance of AI models. It offers end-to-end visibility of structured and unstructured production models and enables a proactive approach towards model management.

To use Censius, follow these steps: 1. Integrate SDK: Register models, log features, and capture predictions using a Java & Python SDK or REST API. 2. Set up monitors: Choose from dozens of monitor configurations to track the entire ML pipeline. 3. Observe: Analyze model drifts, identify root causes of decisions, slice data into cohorts, gain visibility of model performance, build trust with explainability, and understand business ROI.

Censius is an AI Observability and Model Monitoring Platform that helps teams understand, analyze, and improve the real-world performance of AI models.

To use Censius, you need to integrate the SDK with your models, set up monitors to track the ML pipeline, and observe and analyze various aspects of model performance, drifts, decisions, and business impact.

The core features of Censius include automated monitoring and troubleshooting, generative AI monitoring, model monitoring for resolving staleness, model explainability for complex predictions, and Censius Analytics for gauging model performance and impact on business metrics.

Censius can be used to detect and analyze model drifts, perform root cause analysis of model decisions, analyze performance of cohorts, gain end-to-end visibility of model performance, build trust with model explainability, understand business ROI of ML models, monitor data quality and feature distribution, and compare and evaluate multiple model versions.