Analytics AI apps

Open-source GenBI agent: ask in plain language, get governed SQL, charts, and dashboards.

An agentic GenBI platform from Canner that turns natural-language questions into governed SQL, charts, and live dashboards over 20+ databases and warehouses, from BigQuery and Snowflake to PostgreSQL and DuckDB. Its open-source core is a semantic 'context layer' (MDL) that grounds LLM-generated queries in business definitions instead of raw schemas. Runs self-hosted via Docker or as a managed cloud with RBAC and row/column-level security.

An AI spreadsheet where cells run Python, SQL, and JavaScript against live data connections.

Quadratic is a from-scratch spreadsheet built on Rust, WASM, and WebGL that pairs AI analysis with real code: cells can execute Python, SQL, and JavaScript, and connect to 25+ sources like Postgres, Snowflake, BigQuery, and QuickBooks. Ask questions in natural language and get working formulas, code, and charts back in the grid.

Open-source SQL agent — ask questions in plain English, get accurate SQL on your warehouse.

An open-source Python framework for text-to-SQL: you train a RAG layer on your schema, past queries and documentation, and Vanna generates SQL that actually fits your warehouse, returning results as DataFrames or Plotly charts. Connects to Postgres, MySQL, Snowflake, BigQuery, SQLite and more. Vanna 2.0 adds agent features — lifecycle hooks, middlewares, conversation storage and observability — with an optional hosted cloud for access control and audit logs.

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.

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.

Agentic analytics platform with the Spotter natural-language agent.

An enterprise analytics platform built around search and AI. Its Spotter agent lets users ask questions in natural language and get governed answers on live data, reasoning through each step and checking its own work via a semantic layer. Also ships specialized agents for modeling, visualization, and code, with embeddable governed analytics.

AI-native BI that builds dashboards from plain-English questions.

An AI-native business intelligence platform that connects directly to SQL databases and warehouses. Describe what you want in natural language and it generates the query, picks a chart type, and saves the result to a dashboard. Supports Postgres, MySQL, BigQuery, Snowflake, and 750+ data sources via built-in connectors.

No-code predictive analytics and forecasting for media and agency teams.

A no-code AI platform for building predictive models, forecasts, and audience segments from business data. Users connect a CSV or live source like Salesforce, HubSpot, or Snowflake and build models through chat and drag-and-drop, then generate client-ready reports. Now focused on media agencies and marketing analytics use cases.

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.

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.