Features
AI agent orchestration with natural language queries
Automated event detection and action triggers
Deep analysis across databases, documents, and systems
In-database RAG (Retrieval-Augmented Generation)
Vector embedding generation for unstructured data
Key-value extraction from documents
Object detection for images
Preconfigured workflows for common business tasks
User and rights management for enterprise teams
Integration with major databases and third-party tools
Choice of open-source or commercial AI models
Scheduling and alerting for recurring tasks
Support for structured and unstructured data sources
Deployment via Snowflake Native App
Snowflake Native App with Snowpark Container Services
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
