DataPilot

The SQL workspace that documents your database with AI and writes it back via DDL.

A collaborative SQL workspace with AI that actually knows your database. Connect your schema, generate publication-grade table and column documentation, review changes, and apply updates directly with DDL. Then schedule exports, get Slack notifications, and run in cloud, desktop, or on-prem modes.

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Supported databases: PostgreSQL, SQL Server, MySQL, Amazon Redshift. More databases are coming.

DataPilot catalog AI workspace showing schema context and documentation workflows

How it works

Document with AI

Connect a schema, click Document with AI, and generate publication-grade table and column documentation in seconds. Review suggestions, then apply directly via DDL.

Write and review SQL together

Comments, version history, and variables keep SQL reviewable and shareable. Schedule CSV or Excel exports and receive delivery notifications.

Execute where your data lives

Run in cloud, on desktop, or behind the firewall with on-prem workers. Keep one scheduling workflow regardless of execution mode.

AI assistant

AI that actually knows your schema

Most SQL tools bolt on a generic chatbot. DataPilot injects real schema context before each request: table names, column types, foreign keys, indexes, and existing comments.

Schema Documentation: generate and apply table and column comments via DDL in one click
Query Optimization: ranked recommendations based on real schema relationships and indexes
Fix with AI: diagnose SQL errors with exact context, without invented columns
Understand This Data: explain result sets in plain language with PII-aware masking

See AI assistant details

Team collaboration

Keep SQL work shareable and reviewable with comments, version history, and reusable query variables.

See the workspace

Scheduled exports + Slack

Turn trusted queries into repeatable CSV or Excel deliveries. Send run status and download links directly to Slack.

Explore scheduling

Database structure and diagrams

Browse schemas, tables, and columns, then document them with AI. Build ERD diagrams to map relationships visually.

Open the catalog

Execution options

Run in cloud, on desktop, or behind the firewall with on-prem workers (Enterprise).

See execution options

Guides and playbooks

Learn export best practices, on-prem scheduling basics, and workflow standards for scalable delivery.

Browse guides

Switching from PopSQL in 2026?

Review migration guidance and see what you gain with AI documentation, scheduling, and Slack notifications.

Read the migration briefing

Frequently asked questions

Does DataPilot store my database rows?

No. DataPilot stores query execution metadata, schedules, and exported files. Your rows stay in your database.

How does the AI know my real table and column names?

Schema context is injected before AI requests, including table names, column types, nullability, foreign keys, and existing comments.

Does AI documentation write to my database?

Yes. Approved suggestions are applied through ALTER TABLE and COMMENT ON DDL statements.

Can I run scheduled exports behind the firewall?

Yes. Enterprise includes on-prem workers that execute runs locally and sync run metadata back to the workspace.