Hex

Hex Magic uses large language models to generate SQL and Python code from natural language prompts, debug errors with contextual understanding of your project, and explain complex analytical results in plain English. It is schema-aware, meaning it understands your connected database tables and columns, producing accurate queries without requiring users to memorize table structures.

Hex notebooks support SQL, Python, and R cells within the same project, with reactive execution that automatically updates downstream cells when upstream data changes. This allows teams to combine the strengths of each language — SQL for data extraction, Python for transformation and modeling, and built-in charting for visualization — in a single cohesive workflow.

Any Hex notebook can be published as a polished, interactive data application with parameterized input controls such as dropdowns, sliders, date pickers, and text inputs. Published apps can be shared via link, embedded in other websites or internal tools via iframe, and automatically reflect the latest data when schedules are configured.

Multiple team members can edit a Hex project simultaneously with live cursors, presence indicators, and threaded cell-level comments. Built-in version control tracks every edit with full diff history, branching support for development workflows, and the ability to restore any prior version — eliminating the need for external Git integration for most use cases.

Hex connects directly to Snowflake, Databricks, BigQuery, Redshift, PostgreSQL, and other major databases through managed, admin-configured connections. Query results are cached intelligently to reduce warehouse costs, and connection credentials are managed centrally so individual analysts never need direct access to database passwords or service accounts.