Aporia Launches an Extensible Self-Serve Monitoring Platform to Ensure Responsible AI

Aporia Launches First Ever Root Cause Analysis Tool for Real-Time Production Data Investigation

Aporia’s self-serve monitoring platform equips data science teams with the customizable technology they need to properly track every type of ML model in production, for free

Aporia, the customizable ML monitoring platform, announced the launch of the first self-serve monitoring platform for machine learning, free and available to the public. Aporia’s new self-serve product empowers data scientists and ML engineers to begin implementing monitoring logic for early detection of issues like data drift, unexpected bias and performance degradation, and build their very own monitoring system for their ML models within minutes of entering the platform.

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The reasoning for releasing this new self-serve product was to create a platform that is completely customizable and extensible at its core, with an API-first approach.

“Our new self-serve product is a build-it-yourself option that offers full transparency with zero hassle. You can maintain full control of your ML models in production, and you will be able to build your own customizable monitoring solution for early detection of any issues,” says Liran Hason, CEO of Aporia.

Another reason behind deploying the brand new self-serve monitoring system is to address a common issue plaguing the current landscape of existing products in the AI market today. The digital experience of searching for a model monitoring platform is often confusing and misleading, driving users through a complicated sales process before they ever get the chance to test the product. For users, this creates a lot of grey area and uncertainty about the actual functionality of the solution that is being offered.

Using this new self-serve product, Aporia can ensure an optimal experience for data science teams who want to quickly monitor their machine learning models in production immediately. With a low touch approach, data scientists can easily sign up and be onboarded onto the platform in no time at all. Chat support is available if someone requires assistance, but there is no need to speak to anyone if users prefer not to. Furthermore, there is no tedious process to try out the platform. The entire experience is designed to be extremely simple, clear and transparent.

The platform offers 100% visibility in production and enables data scientists to easily build custom monitors for early detection of concept drift, data integrity and production issues in their models. Aporia’s self-serve platform can be seamlessly deployed in under five minutes, and teams can choose from a choice of cloud or self-hosted deployment to ensure the highest level of data security.

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