Atlan emerged in 2019 from SocialCops, an Indian data intelligence company that had spent years building data infrastructure for governments and nonprofits. The founders realized that the biggest challenge in modern data teams wasn’t building pipelines or dashboards — it was understanding what data existed, who owned it, and whether it could be trusted.
Atlan positions itself as an active metadata platform, essentially a collaborative workspace for the modern data stack. Think of it as the control plane that sits on top of your data warehouse, BI tools, ETL pipelines, and ML platforms, providing a unified view of your entire data ecosystem.
The platform automatically catalogs data assets by connecting to tools like Snowflake, dbt, Looker, Tableau, Airflow, and dozens of others. It maps column-level lineage — you can trace how a metric in a dashboard connects back through transformations to source tables. When someone changes a dbt model, Atlan shows you every downstream dashboard and report that might break.
Data discovery works through search, browsing, and AI-powered recommendations. Analysts find datasets with descriptions, quality scores, ownership information, and usage patterns. Business glossaries define metrics consistently across teams, preventing the “my revenue number doesn’t match your revenue number” problem.
Atlan raised $105 million in funding and serves data teams at companies across financial services, e-commerce, and technology. The platform integrates with the tools data teams already use rather than replacing them, which lowers adoption barriers. For organizations where data team productivity is bottlenecked by “where’s that data?” conversations in Slack, Atlan provides the organizational layer that the modern data stack was missing.
