How to Build AI Agents on Customer Warehouse Data: Snowflake, BigQuery, and Supabase

Building AI agents that operate on customer warehouse data involves integrating with various data storage solutions like Snowflake, BigQuery, and Supabase, which typically requires managing different authentication models, query interfaces, and change-detection mechanisms. The Unified Datastore API simplifies this process by offering a single interface to perform essential operations such as reading, querying, writing, and reacting to data changes. This approach enables agents to execute the complete data handling loop across multiple warehouses using a unified object model, thus allowing consistent agent logic regardless of the data warehouse platform. The API supports both structured filtering and raw SQL queries, ensuring compatibility and flexibility across different SQL dialects. The agent development is further streamlined by delegating the complexities of data access and query translation to Unified, while developers focus on agent-specific logic, decision-making, and integration with other data sources.