Agentic Control Center for Data Product Optimization
This work addresses the problem of automating data product creation for end users, but it appears incremental as it builds on existing concepts of AI agents and human-in-the-loop controls.
The paper tackles the challenge of automating data product improvement, which typically requires manual effort from domain experts, by proposing a system that uses specialized AI agents in a continuous optimization loop to enhance data products.
Data products enable end users to gain greater insights about their data by providing supporting assets, such as example question-SQL pairs which can be answered using the data or views over the database tables. However, producing useful data products is challenging, and typically requires domain experts to hand-craft supporting assets. We propose a system that automates data product improvement through specialized AI agents operating in a continuous optimization loop. By surfacing questions, monitoring multi-dimensional quality metrics, and supporting human-in-the-loop controls, it transforms data into observable and refinable assets that balance automation with trust and oversight.