ModernQuery

Users type questions like 'What were our top ten customers by revenue last quarter?' or 'Show me churn rate by plan type for the past six months,' and ModernQuery translates the intent into accurate, optimized SQL, executes the query against connected data sources, and returns results in an easy-to-read table or visualization.

This capability eliminates the analyst bottleneck that slows down data-driven decision-making in most organizations.

The platform connects to popular data warehouses and databases including BigQuery, Snowflake, Redshift, PostgreSQL, and MySQL, and learns the specific schema, table naming conventions, and business logic of each connected data source over time.

This schema awareness is what separates ModernQuery from generic AI SQL generators it understands that 'revenue' in your database lives in a specific column with specific calculation rules, and generates queries that reflect that institutional knowledge rather than making generic assumptions.

Administrators can also define semantic layers that map business terms to technical database concepts, further improving query accuracy.

ModernQuery includes a query history and sharing feature that lets analysts save verified queries as templates, allowing colleagues to run parameterized versions changing date ranges or filtering by team without needing to understand the underlying SQL.

For teams that want to maintain governance over data access, row-level security and role-based query permissions ensure that users only see data they are authorized to view.