SQL Mocker demo
See how SQL Mocker creates SQL from natural-language questions.
Watch a short walkthrough of SQL Mocker's two workflows: generate SQL tailored to your data using a safe copy of your schema, or explain, review, refine, optimise, and troubleshoot an existing query.
Schema to SQL
What the SQL generation workflow covers
01
Add schema metadata
Upload, build, paste, or extract the tables, columns, data types, keys, and relationships that describe your database.
02
Review the structure
Confirm the schema and relationship paths before SQL is generated, and hide columns you do not need in the active context.
03
Ask a question
Describe the result you need using natural language. SQL Mocker creates SQL tailored to the reviewed database structure.
04
Review before use
Check the generated SQL and dummy-data results before copying the query into your database or reporting tool.
Workflow one
Create SQL tailored to your schema
SQL Mocker uses reviewed schema metadata, relationships, and generated dummy data to create SQL from natural-language questions. Your database credentials and production rows are not required.
Explore natural language to SQLWorkflow two
Review and improve existing SQL
Upload an existing SQL file or paste a query, then ask the assistant to explain, review, refine, optimise, convert, or troubleshoot it without connecting AI directly to your database.
Explore SQL review and improvementWhy SQL Mocker uses a safe schema copy
SQL Mocker is designed for people who want help creating or reviewing SQL without granting an AI assistant direct access to a live database.
The schema copy contains the structure needed to understand tables, columns, data types, keys, and relationships. Generated dummy rows provide a preview for checking joins, filters, aggregations, and output columns. You should still review and validate generated SQL before using it with real data.