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Enterprise AI agents can now generate valid, high-fidelity tabular data for training and evaluation without needing access to sensitive schemas or real systems, bypassing critical industry bottlenecks.
EdgeGen is a synthetic task generation framework that extracts compliance rules from an agent's specification and uses them to generate database-grounded edge-case tasks designed to violate these rules, and when combined with existing synthetic data generation techniques, enables agent improvement through finetuning and harness optimization.
