Beans is a collaborative data analysis platform that enables teams to import, transform, and visualize data without relying on SQL engineers. The tool combines a real-time shared canvas, visual transformation pipelines, and live-updating charts, with unlimited version history for easy rollbacks. It supports CSV, Excel, TSV, and JSON file imports, making it accessible for both simple questions and technical analytics.
Funding
Funding not disclosed
Founders
Product
Problem
Teams often share data by sending spreadsheet files back and forth over email or Slack, leading to version confusion, broken context, and delayed analysis. Non-technical users frequently depend on SQL engineers for even basic data transformations, creating bottlenecks and slowing decision-making.
Solution
Beans provides a real-time collaborative canvas where teams can import, transform, and visualize data together. It replaces file-based sharing with live cursors, tables, charts, and edits visible to all collaborators simultaneously. Users can chain filters, sorts, groups, and joins into a visual pipeline—no SQL required—while also having the option to drop into raw SQL for more advanced queries. Charts connect directly to tables and update automatically as transformations change, and every action is saved to unlimited project history for one-click restoration of any previous version.
Target Audience
Primary users are data analysts, product managers, and business operations teams who need a collaborative, self-serve data analysis tool without depending on dedicated data engineering resources.
Features
- Real-time multiplayer editing with visible cursors, tables, charts, and edits on a shared canvas
- Visual transformation pipeline that chains filters, sorts, groups, and joins without requiring code
- Raw SQL mode for users who need more technical control beyond the visual interface
- Live chart connections to tables that refresh automatically when underlying transforms change
- Unlimited project history with preview and one-click restore of any prior version
- Instant import support for CSV, Excel, TSV, and JSON file formats
- Built-in formulas for computing derived columns across rows using spreadsheet-style logic