Features
AI agent searches and navigates the web
Build datasets from scratch without input data
Natural language prompt-based extraction
Structured outputs in consistent formats
Schedule projects for change monitoring
API-first delivery for single or bulk records
Handles bot detection and dynamic sites
Contact data and profile enrichment
List building per result (2-4 credits)
Web scraping per page (0.05 credits)
Supports websites, PDFs, and third-party APIs
No-code UI for non-engineers
Enterprise-grade reliability without infrastructure overhead
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
