Describe Your Transformation
Tell us what you want to do in natural language, and AI will generate the SQL
Example Transformations
Click any example to try it out
How Natural Language SQL Works
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1Understanding Intent
AI analyzes your natural language description to understand the transformation logic
2SQL Generation
Generates optimized, production-ready SQL code that implements your requirements
3Validation & Testing
AI validates syntax and provides example outputs to ensure correctness
4Confidence Scoring
Each result includes a confidence score to help you assess reliability
Best Practices
- • Be specific about units and formats (e.g., "millions", "2 decimals")
- • Mention data types if relevant (e.g., "string", "date", "number")
- • Include edge cases in your description (e.g., "if null, return 0")
- • Always test generated SQL with sample data before production use
Supported Operations
What you can build with Natural Language SQL
Mathematical
Addition, subtraction, multiplication, division, rounding, percentages
String Operations
Concatenation, substring, upper/lower case, trimming, splitting
Date & Time
Date formatting, age calculation, date arithmetic, extraction
Conditional Logic
If-then-else, case statements, null handling, default values
Type Conversion
String to number, date parsing, boolean conversion, casting
Aggregation
Sum, average, count, min, max, grouping operations