# Eizen Observability Eizen Observability is an ML Observability platform for business managers and ML practitioners to observe and optimize their machine Learning models in production. Machine learning observability is the process of understanding the model’s behavior and performance throughout its lifecycle. The Eizen Observability platform records the model's data in real time for monitoring and detecting any anomalies in the data in production, explainable AI for model explainability, and optimizes model performance by automating the retraining process. ### Eizen Observability platform can help you in - * Analyzing model’s performance in real time * Compare the performance of the model with different metrics and time periods * Checking data drift in real time and notify the user when a drift is detected * Retraining modes to automate the retraining process and optimize the model’s performance * Explainable AI for explaining predictions to build trust --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://eigenmaps.gitbook.io/eizen-observability/eizen-observability.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.