CastorDoc is a proud sponsor at the Gartner Data and Analytics Summit. Bringing together the best minds, technologies and leaders working on the front line of analytics innovation, CastorDoc will showcase its data assistant powered by enterprise-grade governance.
CastorDoc stands out as the only AI assistant powered by data governance. Our platform integrates advanced governance, cataloging, and lineage capabilities with a user-friendly data assistant. This creates a powerful tool for businesses to enable self-service analytics.
Interested in a one-on-one discussion? Click here to schedule your exclusive demo or simply fill up the form on this page.
Build a lean & discoverable data stack powered by a modern data catalog
Find the data you need, when you need it. Easily search for assets and discover how your all your data fits together and into the bigger picture.
The modern data catalog with all the bells and whistles. Automate documentation by integrating with your entire data stack and ingesting your metadata within minutes.
Easily access column lineage across all your tools. See the high level overview of your pipelines to build trust and view how changes affect downstream assets.
Keep your data stack lean by optimizing for performance and costs, while maintaining compliance and security across all your data.
Documentation is a painful process, we thus think it should be crowdsourced as much as possible, just like Wikipedia."
Employees, more than half of the company, uses CastorDoc on a monthly basis.
I could not imagine reducing the number of questions we got from stakeholders was possible before we had a data catalog"
increase in team productivity with CastorDoc
I can give CastorDoc to anyone in the company and I know that they won’t ask any questions."
decrease in data-related slack pings to the data team thanks to CastorDoc
“[I like] The easy to use interface and the speed of finding the relevant assets that you're looking for in your database. I also really enjoy the score given to each table, [which] lets you prioritize the results of your queries by how often certain data is used.” - Michal P., Head of Data