One AI engine that connects to your data — spreadsheets and databases — and turns a plain-English question into an answer, a chart, and a dashboard. Live, synced, and across every source at once.
Connect Google Sheets and Excel files directly, or point tableArth.ai at a database. Your analysis runs on live data that stays in sync, instead of a one-time upload that goes stale.
Ask in plain English. tableArth.ai writes the query, runs it against your data, and returns the answer. SQL for relational databases, the right query for a document store — no SQL, no schema knowledge, no training data required.
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tableArth.ai understands files with multiple tabs and databases with multiple tables. Ask a question that spans them and it joins related data automatically — the way you would across database tables, with no VLOOKUP and no flattening into one sheet first.
A Workbook keeps multiple sources connected and synced in one place. Ask one question in natural language and the engine pulls data across all of them to return a single, unified answer — always current, no re-uploading.
Eight chart types, one engine. tableArth.ai chooses the right one based on the question and the shape of the answer — no chart config from you.
Compare categories
Trends over time
Cumulative growth
Visualize proportions
Reveal correlations
Multi-dimension breakdown
Process drop-off
Detail & raw data
tableArth.ai suggests relevant questions for your data, so users never face a blank box and always have a strong place to start exploring.
When a request is ambiguous, tableArth.ai asks a quick clarifying question instead of guessing — so you get to the right answer faster and with more confidence.
Answers stream token-by-token and typically resolve in under five seconds, so nothing sits on a spinner. Every dataset also gets an auto-built dashboard — KPIs, trends, and breakdowns, chosen by the engine.
A generated query self-corrects up to three times before an error ever reaches the user — column name fixes, type coercions, join repair, and dialect adjustment.
Google Sheets, Microsoft Excel files, and databases including MySQL, PostgreSQL, MongoDB, and Druid, plus CSV and Excel uploads. Connected sources stay live and sync automatically in a Workbook, so your analysis is never a one-time snapshot.
Yes. tableArth.ai understands files with multiple tabs and databases with multiple tables, joins related data automatically, and with a multi-source Workbook answers one question across every connected source at once.
Yes. The engine writes the query from your plain-English question — SQL for relational databases, the right query for a document store like MongoDB — runs it, and returns the answer with a chart. No SQL knowledge is required.
tableArth.ai auto-selects the right visual across bar, line, area, pie/donut, scatter, stacked bar, funnel, and plain table. You don't configure chart types — the engine picks the one that fits the question.
It suggests relevant questions for your data so you always have a starting point, and asks a clarifying question when a request is ambiguous — so you get to the right answer faster and with more confidence.
The engine has retry intelligence — it detects a failed or invalid query and self-corrects, retrying up to three times before falling back gracefully, so a single bad query doesn't surface an error.
Start with one sheet or one database — connect it, ask in plain English, and see an answer and a chart in seconds.
