Features
Natural language querying across connected data sources
Unified semantic layer for consistent business definitions
Automated report generation and scheduling
Drag-and-drop dashboard builder
Role-based access control and data governance
100+ data source connectors (SQL, cloud apps, APIs)
AI-driven data lineage and anomaly detection
Embedded analytics for customer-facing portals
Collaborative annotations and shared workspaces
On-premise deployment option
Slack and Teams integrations for conversational querying
Automated alerting on data anomalies
High-fidelity synthetic data generation via TabularARGN
Agentic data science automation for training/sampling
Natural language AI Assistant executing Python code
Mock data generation for safe experimentation and testing
Simulated data for edge-case and what-if modeling
Multi-table synthesis with referential integrity
Time-series support and data rebalancing
Differential privacy with temperature control
Deployment on Kubernetes or Red Hat OpenShift
Open-source Synthetic Data SDK under Apache v2 license
Data connectors for Databricks, AWS, Snowflake, BigQuery
Real-time data access from production systems (e.g., Databricks)
Star schema and nested sequences support
REST API and Python Client for programmatic access
Conditional simulation and seeded generation
