While we have not gone extremely deep into all the features that Whylabs provides, we have had extraordinary 1:1 technical support. They are quick to respond, fast at finding solutions, and eager to make improvements for your use case.

As an AI consulting and services firm, we’re always on the lookout for tools that our customers can leverage to improve their adoption of AI. Model monitoring and maintenance are big needs for any company actively investing in AI that wants to turn those investments into returns. We’ve been testing out WhyLabs as a potential observability solution and have been impressed with its capabilities. Their recent platform expansion with LLM observability and guardrails aligns well with the Gen AI capabilities that are becoming important to many of our customers. WhyLabs offers a wide range of functionality, including data profiling, model monitoring, alerting, and root cause analysis. The platform covers many of the end-to-end workflow needs of an ML team. A key part of their approach is the open-source whylogs library for local data profiling. Rather than sending raw data to the cloud, whylogs lets you summarize on-premises before sending compact statistical profiles. Contrary to some other monitoring solutions, this aligns very well with many of our clients’ strict data privacy expectations. whylogs itself is straightforward to integrate and use. You can add monitoring to a pipeline with minimal fuss. As an open-source tool, it provides transparency into what’s being tracked and how. On the support side, we’ve found the WhyLabs team extremely nice and responsive. The platform documentation is fairly comprehensive as well. Another key plus is that we found their pricing model really fair. For teams looking for an observability solution, WhyLabs is definitely worth a close look. The platform covers a wide range of ML workflow needs, and their approach to data privacy is a plus. We look forward to using it more broadly!

We recently integrated the WhyLabs AI Observatory into our team's model serving platform to monitor input features and model scores in near real-time. I was impressed by its seamless integration and range of capabilities. They provided some good examples, so it was easy to integrate monitoring of our data. I also like the large amount of monitors and dashboards to debug various aspect of ML data and models. We set up alerts through Slack which was also easy to set up. The alerts are useful to detect issues with our model's features such missing data. We also watch WhyLabs dashboards when deploying new model versions to ensure a smooth rollout. Another highlights is is user interface. It's user-friendly, clear, and intuitive. They have some preset monitors that are easy to add with just a few clicks. I noticed they added more preset monitors recently which shows their rapid innovation. Finally, and what I like the most, is its customer support. The team is responsive, and they are always ready to assit, and they quickly reply for any questions or help we ask.