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Generate high-quality synthetic data from scratch or seed datasets.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "DataDesigner" yet — see the docs or source repo.
Generate 500 rows of high-quality synthetic test data for an e-commerce order system. Include order ID, user ID, product category, amount, payment method, order time, and order status. Make the distribution realistic and include a small number of outliers.
A well-structured synthetic order dataset with realistic distributions for testing or demos.
Using these 20 customer support conversation samples, generate 200 synthetic records with consistent style but non-duplicate content. Preserve the original intent labels and add variation in tone and phrasing.
A richer synthetic conversation dataset aligned with the seed samples for model training or evaluation.
Generate a synthetic medical appointment dataset for internal analytics demos. Do not include any real personal information, but preserve statistical characteristics such as age group, department, appointment time, and visit outcome.
A synthetic medical appointment dataset that avoids real sensitive data while preserving key statistical patterns.
Estimate, validate, and generate layouts for Rubin-era data center designs.
Generate multi-table synthetic data matching exact revenue curves and fraud rates.
Run end-to-end data science workflows through natural language commands.
Generate UI design rules, color palettes, and brand design references.
Capture TouchDesigner networks and get context-aware analysis and suggestions.
Generate modern APIs and MCP tools for Azure and on-prem databases.