What Is AI Usage Data. How Enterprises Can Collect It.
Learn what AI usage data includes, how enterprises collect and track it, and why centralizing usage metrics is key to measuring AI adoption and ROI.
Visualize end-to-end configuration of your data flows and navigate across sources, data sets, and destinations. Establishing and monitoring data pipelines are essential activities for effective DataOps. Now you can see a quick pipeline view of all your data flows in Nexla. Click into the detail view of any resource to learn more about it—where it came from, data volumes, types, attributes, and where the data is going. Pause and activate pipelines to fix issues or make edits
Nexla now supports the ability to create a webhook right in the UI for use in other services. This allows other services to easily send data to Nexla.
You can now configure notifications and alerts on individual data sources, data sets, and destinations. Select when you’d like to be notified based on changes in data. Receive improved notification emails with deep links to relevant resources.

As inter-company data grows, so too do the number of pipelines companies must manage. Use tags (keywords) to help organize your data sets, sources, and destinations. Then search for tags to easily find the resources you are looking for. Very handing when working with colleagues across the organization!

Read the complete release notes for more product updates!
Learn what AI usage data includes, how enterprises collect and track it, and why centralizing usage metrics is key to measuring AI adoption and ROI.
Reusable data products unify databases, PDFs, and logs with metadata, validation, and lineage to enable join-aware RAG retrieval for reliable GenAI applications.
Governed self-service data embeds metadata controls, quality guardrails, and access policies. This enables business users to explore and transform data in no-code while preventing metric drift.