⚡ NEW · SYLVAERA

Prompt → Dataset

Describe your dataset in plain English — get realistic, structured data instantly via Claude Sonnet on AWS Bedrock.

Quick Examples
Dataset Settings
Rows25
Simulate Nulls %0%
Refine Last Result

Your dataset will appear here

Choose a quick example or describe your desired dataset structure on the left, then click Generate.

👤 Users & Locales
Generates region-specific addresses, phone formats, and names.
🛒 Business Entities
Describe e-commerce orders, customer support threads, or transaction logs.
🔧 Refine Iteratively
Refine fields or inject anomalies dynamically without regenerations.

AI-Powered Prompt-to-Dataset Generator

Need mock user lists, product reviews, or logs? Instead of relying on rigid, pre-generated datasets, this tool utilizes advanced LLMs (Claude Sonnet on AWS Bedrock) to convert natural language descriptions directly into high-fidelity structured data.

Supported locales and custom parameters

By setting specific settings, you can tailor the localization of addresses, currency codes, phone number formats, and names to fit target requirements.

  • Indian Locale: Generates realistic Indian names, mobile numbers, Aadhaar IDs, and INR currencies.
  • USA / UK Locales: Returns standard US zip codes, UK postal codes, phone structures, and USD/GBP amounts.
  • Null Simulation: Inject realistic, incomplete fields (ranging from 0% up to 30% nulls) to test how your backend handles sparse inputs.

FAQ

Can I edit or add columns to generated data?

Yes. Simply use the Refinement panel on the left and enter instructions like 'add a column for registration status with active/inactive values' and click Apply Refinement.

Is there a limit on the number of fields?

No. You can ask for as many columns as needed. The AI will automatically map logical schemas based on your prompt descriptions.

What export options are available?

We support downloading datasets as raw CSV files, formatted JSON arrays, SQL INSERT statements ready for database execution, or Python lists of dictionaries.