Enable data teams to find, understand, and use enterprise data through natural language while auto-generating SQL, Python, and ETL workflows. Reduce data delivery timelines by 56% across Riyad Bank's ...
Join Waiting listDiscovers relevant datasets and tables using semantic understanding of business terminology
Traces data origins, transformations, and dependencies enabling complete understanding of data quality
Generates production-ready query and transformation code from natural language requirements
Auto-creates data workflows and pipeline specifications for loading and transforming data
Defines scheduling rules and monitoring alerts for automated pipeline execution
Connects to Oracle data warehouses, ETL tools (Informatica), and analytics platforms (SAS, DataRobot)
Automated code generation replaces manual SQL and ETL development reducing timelines
Generated code follows standards and quality checks reducing production data errors
Service Enablement - Semi-technical users handle own data queries reducing dependency on data team bottlenecks

Turn operational complexity into measurable performance gains.