Trace any number back to where it came from.
When someone asks how a metric was calculated, you shouldn't have to open every SQL file to answer. SQLExplain maps how your files connect and traces any metric back to its source, in plain language.
Before anything reaches the AI, we mask your database, schema, and table names, and every hardcoded value (text, dates, numbers). Your column names stay, so the explanation still makes sense.
Visualize how your SQL files connect
One diagram shows the whole pipeline, from source tables to final output, so you never read file after file again.
Follow the data lineage in plain English
A clear, step-by-step account of how each measure is built, from its source columns to the final result.
Trace a metric back to its source
Pick any metric, like revenue, active users, or conversion rate, and trace it back across every file to exactly what built it. The part a chatbot guesses at and gets wrong.
How it works
Paste or upload SQL
One query, or a full project of connected files.
SQLExplain parses it
A real SQL parser builds a structural map before any AI sees it.
Read the explanation
Plain-English summary, step-by-step logic, and a field-level trace.
Built differently from a general chatbot
A general chatbot sends your table names and real values to a third party and guesses at joins and grain. SQLExplain parses your SQL first, builds a structural model of every table, join, and calculation, and the AI explains that model instead of inventing it.