--- title: Improving search relevance with ML monitoring description: Let's take a dive into ML systems for ranking and search relevance and what it means to monitor them for quality, edge cases, and corrupt data. image: https://go.superwise.ai/hubfs/Improving%20search%20relevance%20with%20ML%20monitoring.png --- [![Colors - Logo_Superwise - Standard](https://go.superwise.ai/hubfs/Colors%20-%20Logo_Superwise%20-%20Standard.svg "Colors - Logo_Superwise - Standard")](http://superwise.ai) [![White - Logo_Superwise - Standard](https://go.superwise.ai/hs-fs/hubfs/White%20-%20Logo_Superwise%20-%20Standard.png?width=809&height=174&name=White%20-%20Logo_Superwise%20-%20Standard.png "White - Logo_Superwise - Standard")](http://superwise.ai) ![menu-1](https://f.hubspotusercontent20.net/hubfs/6667626/menu-1.svg) ## Improving search relevance with ML monitoring ![Gad headshot_LP](https://go.superwise.ai/hs-fs/hubfs/Gad%20headshot_LP.png?width=217&height=264&name=Gad%20headshot_LP.png) ### Gad Benram Founder & CTO TensorOps April 19th 1:00 PM ET ## Webinar When building machine learning systems for ranking and search relevance, it's crucial to measure the quality of the results for ongoing improvement of your models. Furthermore, you have to be able to identify edge cases in which your models are wrong, as well as detect corrupt data before it's exposed to users.   In this session, we'll show how you can track search results quality on architectures such as Elasticsearch and vector databases like Pinecone.   #### About our speaker 👂 Gad is the founder and CTO of [TensorOps](https://tensorops.ai/). The company offers expert services for AI-driven search applications as well as question-answering and chat.       [![White - Logo_Superwise - Standard](https://go.superwise.ai/hs-fs/hubfs/White%20-%20Logo_Superwise%20-%20Standard.png?width=809&height=174&name=White%20-%20Logo_Superwise%20-%20Standard.png "White - Logo_Superwise - Standard")](http://superwise.ai) All rights reserved to Superwise 2026 - - -