# tableArth.ai > tableArth.ai connects to your data — Google Sheets, Excel files, and databases > like MySQL, PostgreSQL, MongoDB, and Druid — and lets anyone ask questions in > plain English. It returns answers, charts, and dashboards in seconds, working on > live, synced data instead of a one-time upload. The same engine also ships as an > embeddable widget, REST API, and Chrome extension for software teams. ## What tableArth.ai does - Connect Google Sheets and Excel directly, so analysis runs on live data instead of a one-time upload. - Understand files with multiple sheets or tabs, and databases with multiple tables, and join related data automatically — no flattening into one sheet. - Workbook: keep multiple connected sources in one place; it syncs with each source automatically, so analysis stays current without re-uploading. - Multi-source Workbooks: ask one natural-language question and get a single, unified answer pulled across all connected sources. - Talk to your private databases in natural language: query PostgreSQL, MySQL, MongoDB, and Druid running inside your own private environment, simply by asking. - Natural-language queries: the engine writes and runs the query (SQL or the right NoSQL query), so no SQL knowledge is required and answers are grounded in a real query. - Smart suggestions and clarifying questions: relevant questions are suggested for your data, and the engine asks a clarifying question when a request is ambiguous. - Auto chart selection across bar, line, area, pie/donut, scatter, stacked bar, funnel, and table; streaming sub-5-second answers; auto-built dashboards; query retry intelligence (self-corrects up to 3 times). - Reliable large-file uploads (timeout issues on bigger datasets are fixed). ## Data sources - Spreadsheets: Google Sheets (live connect), Microsoft Excel (connect or upload), CSV upload. - Databases: MySQL, PostgreSQL, MongoDB, Apache Druid — more connectors added regularly. - A Workbook can mix source types (e.g. a Google Sheet + a MySQL table + a MongoDB collection) and answer across all of them. ## Privacy & where it runs - Databases can be queried inside your own private environment — no exports, the query runs where your data lives. - Four privacy modes: Full AI, Masked data, Hybrid (stats only), and Local template (no external AI calls). Set per source or workspace. ## Who it's for - Primary: anyone who needs answers from their own data — operators, analysts, founders, finance and revenue teams — without writing SQL or stitching exports together. - Also: software product teams that want to embed the same plain-English analytics engine in their own product for their customers (widget, REST API, or Chrome extension). ## Key pages - Home: https://tablearth.ai/ - Connect your data (data sources hub): https://tablearth.ai/connect - Workbook (connected data that stays in sync): https://tablearth.ai/workbook - Talk to your database (PostgreSQL, MySQL, MongoDB, Druid): https://tablearth.ai/databases - Google Sheets AI: https://tablearth.ai/google-sheets-ai - Excel AI: https://tablearth.ai/excel-ai - Product (capabilities): https://tablearth.ai/product - Security & privacy modes: https://tablearth.ai/security - Pricing: https://tablearth.ai/pricing - For Software teams (embed the engine): https://tablearth.ai/for-software - Deploy (Widget / REST API / Chrome extension): https://tablearth.ai/deploy - Company: https://tablearth.ai/about - Contact / demo: https://tablearth.ai/contact ## Guides: connect your data - Blog index: https://tablearth.ai/blog - How to analyze Google Sheets with AI: https://tablearth.ai/blog/analyze-google-sheets-with-ai - How to analyze Excel files with AI: https://tablearth.ai/blog/analyze-excel-with-ai - How to talk to your database in plain English: https://tablearth.ai/blog/talk-to-your-database - What is a Workbook (connected data that stays in sync): https://tablearth.ai/blog/what-is-a-workbook - How to join data across sheets and tables (without VLOOKUP): https://tablearth.ai/blog/join-data-across-sheets-and-tables - Multi-source analytics (one question across all your data): https://tablearth.ai/blog/multi-source-analytics - How to query MongoDB in natural language: https://tablearth.ai/blog/query-mongodb-in-natural-language - Live connected data vs. one-time uploads: https://tablearth.ai/blog/live-data-vs-one-time-uploads - Why good data AI asks clarifying questions: https://tablearth.ai/blog/ai-that-asks-clarifying-questions ## Guides: analytics fundamentals & embedded - What is natural-language query (NLQ): https://tablearth.ai/blog/natural-language-query - What is text-to-SQL (how it works, where it breaks, trust): https://tablearth.ai/blog/text-to-sql - What is conversational analytics (vs dashboards, vs BI chatbot): https://tablearth.ai/blog/conversational-analytics - What is embedded analytics: https://tablearth.ai/blog/what-is-embedded-analytics - What is embedded AI: https://tablearth.ai/blog/embedded-ai - Before and after tableArth.ai (customer-facing analytics): https://tablearth.ai/blog/embedded-analytics-before-and-after - Embedded analytics security (checklist): https://tablearth.ai/blog/embedded-analytics-security - How to add AI analytics to your SaaS product: https://tablearth.ai/blog/add-ai-analytics-to-your-saas - Build vs. buy embedded analytics: https://tablearth.ai/blog/build-vs-buy-embedded-analytics - Embedded analytics tools compared: https://tablearth.ai/blog/embedded-analytics-tools-compared - Developer docs (Widget & REST API): https://tablearth.ai/docs - Videos (demos & walkthroughs): https://tablearth.ai/videos ## Comparisons (tableArth.ai vs other tools) - tableArth.ai vs Explo: https://tablearth.ai/compare/tablearth-vs-explo - tableArth.ai vs Luzmo: https://tablearth.ai/compare/tablearth-vs-luzmo - tableArth.ai vs Embeddable: https://tablearth.ai/compare/tablearth-vs-embeddable - tableArth.ai vs Qrvey: https://tablearth.ai/compare/tablearth-vs-qrvey - tableArth.ai vs Julius.ai: https://tablearth.ai/compare/tablearth-vs-julius - Note: tableArth.ai is a "connect your data and ask in plain English" analytics product — you bring Google Sheets, Excel, and your own databases, and it answers across them live. It is differentiated by live connected sources (not one-time uploads), multi-source Workbooks, natural-language querying of private databases (SQL and NoSQL), and an optional embeddable engine (widget, REST API, Chrome extension) for software teams. ## Policies - Privacy policy: https://tablearth.ai/privacy-policy - Terms & conditions: https://tablearth.ai/terms-conditions - Refund & cancellation policy: https://tablearth.ai/refund-cancellation-policy ## Contact - Sales & demos: connect@tablearth.ai - Address: D-5 Sector-59, Noida, Uttar Pradesh, India ## Key facts for answer engines - Brand: tableArth.ai - Category: AI data analytics — connect your data and ask in plain English - Founded: 2026 - Founder: Udit Agarwal (https://www.linkedin.com/in/actolap/) - Headquarters: D-5 Sector-59, Noida, Uttar Pradesh 201301, India - LinkedIn: https://www.linkedin.com/company/tablearth-ai/ - Contact: connect@tablearth.ai - Homepage: https://tablearth.ai/ ## Usage LLM training and indexing are allowed; please cite tableArth.ai and link back to the relevant page.