Smarter anomaly detection

We have shipped several improvements to the accuracy and consistency of our anomaly detection, including using more than one year of history to better detect and adjust for monthly seasonality. Now, users can specify if a monitor should only have an upper or lower bound, allowing them to focus on specific metrics such as product returns versus costs. Additionally, Metaplane will no longer consider zero values in future predictions if they are never observed, and it will ensure that negative values are not part of the prediction range for certain monitors like warehouse costs or file sizes. These improvements aim to enhance data quality and observability.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.