Seek AI is a natural-language data analytics platform founded in 2021 by CEO Sarah Nagy in New York City. It lets business users query enterprise databases by typing plain-English questions, which the platform converts into optimized SQL via its proprietary SEEKER-1 model. No coding is required, so analysts, ops managers, and executives can get answers directly from Snowflake, BigQuery, Redshift, Databricks, and Azure without waiting on a data engineer.
The platform runs a multi-agent architecture that maps questions to a customer's specific database schema, applies reinforcement learning to improve accuracy over time, and delivers results with context. Users can interact through a web interface or through Slack and Microsoft Teams. The system achieved over 90% accuracy on Yale's Spider SQL benchmark, placing first on the leaderboard. It is SOC 2 Type I compliant and supports role-based access controls for enterprise governance.
In June 2025, IBM acquired Seek AI to deepen its watsonx data intelligence offering and integrate the technology into the Watsonx AI Labs accelerator in Manhattan. The acquisition confirmed Seek's position as a serious enterprise-grade tool rather than a consumer experiment. Pricing is enterprise-only and negotiated through IBM's sales channels following the acquisition.
+Supports major data warehouses out of the box: Snowflake, BigQuery, Redshift, Databricks, and Azure Synapse.
+Slack and Microsoft Teams integration lets users pull data insights without leaving their existing workflow.
+SEEKER-1 model self-improves per customer schema, reducing hallucinations and wrong SQL over time through in-context learning.
−Pricing is fully enterprise, negotiated through IBM sales after the acquisition, making it inaccessible for small teams or individual analysts.
−The IBM integration is still maturing, so roadmap visibility and standalone product continuity carry short-term uncertainty for prospective buyers.