Basedash

Agentic analytics notebook for SQL, Python, and R data teams.

A collaborative data workspace combining SQL, Python, and R notebooks with shareable data apps. Its Notebook Agent and Magic AI generate queries, debug code, run exploratory analysis, and build visualizations as editable notebook cells. Built for data teams that need reproducible, governed analysis rather than one-off chat answers.

Chat with your data — an AI data analyst for CSVs, sheets, and DBs.

An AI data analyst that lets you upload CSVs, Excel, and Google Sheets, then ask questions in plain language to clean, analyze, visualize, and model your data. It writes and runs Python behind the scenes and can generate charts, slides, and reports from the results. Pro plans add direct connectors to live databases like Snowflake, BigQuery, and Postgres.

Conversational AI data analysis for files, databases, and the web.

A no-code data analysis tool that turns natural-language questions into instant insights, charts, and presentations. Users upload Excel, CSV, TSV, and SQL files or paste URLs, and the AI handles cleaning, statistical analysis, and visualization with suggested follow-up questions. Supports multi-modal inputs including images and audio.

Conversational analytics over your Databricks lakehouse data.

A no-code conversational analytics interface within the Databricks platform. Business users ask plain-English questions about lakehouse data and Genie returns SQL, charts, and natural-language explanations. It adapts to your business concepts and enforces Unity Catalog governance, so answers stay secure and auditable. Billed through Databricks compute rather than a separate license.