Connecting Pinecone to Monte Carlo allows for monitoring the most critical component of your AI pipelines. We've brought Monte Carlo's data anomaly detection to Pinecone by observing patterns in Vector Count by Index and Index Namespace.
As soon as you connect Pinecone, hourly tracking of Vector Count by each Index and Index Namespace will be cataloged to be view and actively monitored by Monte Carlo's machine learning - no other setup necessary. You can see the expected Thresholds of Vector Count highlighted on the chart as well.
Learn how to setup Pinecone with Monte Carlo in the documentation. More monitors and metadata about your Pinecone assets are coming soon.