I'm excited to share that Snowflake has announced its plans to acquire the Select Star platform. This marks a new chapter in our mission to bring intelligent metadata context to every organization and expand Snowflake Horizon Catalog’s view of enterprise data for agentic AI experiences.
From the beginning, our vision at Select Star has been to make data easier to find, understand, and use. That means not only capturing what data exists, but also where the data comes from, who uses it, and how it’s being used. Whether it was simplifying data governance, accelerating self-service analytics, or cutting down the cost of unused data assets, we’ve seen how powerful metadata context can be. It’s evolved from a nice-to-have to the core of how modern data teams operate.
AI + Data Thrives With Metadata Context
As AI becomes more integrated into organization workflows, context becomes even more critical. A model or agent can only perform as well as the context it has. Without knowing where data originates, how it has been shaped, or which teams depend on it, AI cannot produce reliable results. The foundation of trustworthy AI is trustworthy metadata.
We saw this firsthand as customers have leveraged Select Star’s lineage, popularity, entity relationships, and other connected metadata to supercharge their AI for data. With our universal metadata model that connects more than 25 integrations, our customers have gained a new level of clarity of their data models and their data ecosystem. For us, this reinforced a belief we held from the start: metadata is the connective tissue that turns raw data into something usable and dependable.
This context has become even more important with the rise of AI. Through our work on the MCP (Model Context Protocol) Server, Ask AI, and automated semantic model generation, we watched how powerful AI becomes when it can rely on accurate and up-to-date metadata. These experiences showed us that the next generation of data intelligence will require an embedded metadata layer that sits across the entire data ecosystem.
Joining Snowflake will allow us to take this vision further. One of our priorities will be to bring Select Star’s industry-leading data lineage and data discovery capabilities into Snowflake’s Horizon Catalog, which will help agentic AI experiences like Snowflake Intelligence and Cortex Code deeply understand an enterprise’s data and how to extract insight from it.
Looking Ahead
Expanding our metadata context layer beyond Snowflake and bringing our existing integrations into Snowflake’s Horizon Catalog will give teams a consistent view of lineage, ownership, and usage across every connected system. With that foundation in place, customers can spend more time answering business questions and less time stitching together the story behind their data. It becomes easier to identify the right datasets, avoid redundant work, and confidently support business initiatives across the organization.
I am excited to scale our impact and continue building the kind of data intelligence platform we always envisioned. I’m deeply grateful to our customers, our team, and our investors for being a part of our journey, and looking forward to what we will create together with Snowflake.
