Sales pipeline
Won revenue$300.6KSeptember 2026 · Sample
Focus sales effort on productive channels.
Explore dashboard
AI native · Connect your data
Connect your data.
Connect your data.
Give AI the context.
Spreadsheets, nine database engines, cloud billing, advertising, Tally, and private sources. Bring the right data into a workbook, then explore twelve dashboard examples for every connector.
Q3 Revenue Workbook
Ask
Sources
Sheets
PostgreSQL
You
Combine the sales sheet with our orders DB — revenue by region this quarter?
APAC leads at $412K, up 31% QoQ,
followed by EMEA at $286K and
NA at $255K. Figures blend the Sheets
pipeline with booked orders from Postgres.
Revenue by region
Q3 · USD
APACEMEANA
LATAMMEAF
AI native analytics · Dashboard libraryOne connection.
One connection.
Twelve ways to see more.
Start with a business question.
Open a dashboard. See the value in your data.
Illustrative dashboards using fictional September 2026 data. Available analyses depend on the fields in your source.
Campaign scorecard
Campaign spend$55.5KSeptember 2026 · Sample
Compare the campaigns competing for your budget.
Explore dashboardExpense tracker
Recorded expenses$119.1KSeptember 2026 · Sample
Find the cost categories worth discussing.
Explore dashboardProject effort
Hours logged6.7KSeptember 2026 · Sample
See how delivery effort is distributed.
Explore dashboardHiring activity
Applications received5.3KSeptember 2026 · Sample
Review hiring activity by role.
Explore dashboardStore performance
Store sales$198.2KSeptember 2026 · Sample
Make store reviews more focused.
Explore dashboardInventory movement
Units shipped26.3KSeptember 2026 · Sample
Guide the next stock and fulfillment discussion.
Explore dashboardCustomer collections
Receipts$208.6KSeptember 2026 · Sample
Understand the rhythm of incoming payments.
Explore dashboardSupport desk
Tickets opened10.1KSeptember 2026 · Sample
Plan support coverage using demand patterns.
Explore dashboardPurchase tracker
Purchase value$164.3KSeptember 2026 · Sample
Review high-spend purchasing categories first.
Explore dashboardContent performance
Content views495.7KSeptember 2026 · Sample
Choose what to investigate in your next content review.
Explore dashboardDelivery tracker
Deliveries completed15.5KSeptember 2026 · Sample
Put regional delivery performance in context.
Explore dashboardEvery preview opens a full dashboardTake the question into your AI tools
Connectors & data sources
Your data. More ways in.
From a spreadsheet to a cloud bill: explore every supported source, how it connects, and a dashboard built around its data.
19 connectors & connection options
Spreadsheets
Google Sheets
Connect a sheet, refresh its workbook snapshot, and explore performance across tabs.
Refreshable snapshotSpreadsheets
Microsoft Excel
Analyze uploaded files or a selected range or table through the Excel task pane.
Upload / add-inSpreadsheets
CSV files
Upload tabular exports and turn everyday reporting into questions and reusable charts.
Uploaded snapshotDatabases
PostgreSQL
Explore orders, customers, and revenue with SQL generated from your questions.
Live queryDatabases
MySQL
Ask questions across related tables and see product and store performance.
Live queryDatabases
MongoDB
Explore document collections and product events through natural-language analytics.
Live queryDatabases
Microsoft SQL Server
Turn operational tables into views of shipments, warehouses, and fulfillment.
Live queryDatabases
Oracle
Explore enterprise finance tables, invoice values, and business-unit reporting.
Live queryDatabases
Snowflake
Ask questions over warehouse data and build views around your business definitions.
Live queryDatabases
ClickHouse
Explore large event tables with time-series charts and traffic breakdowns.
Live queryDatabases
Apache Druid
Analyze time-oriented datasets, event volumes, and dimensions in Druid.
Live queryDatabases
Supabase
Explore the application data in your Supabase Postgres database.
Live queryCloud billing
AWS Billing
Import CUR 2.0 Parquet exports from S3 with an IAM role or supported access keys.
Daily / manual refreshCloud billing
Azure Billing
Import Cost Management FOCUS Parquet exports from Blob Storage using a Read/List SAS token.
Daily / manual refreshCloud billing
Google Cloud Billing
Read standard or detailed native billing exports from BigQuery with a service account.
Daily / manual refreshAdvertising
Google Ads
Explore campaign, keyword, search-term, device, geography, and other supported reports.
Assisted rollout · read onlyAdvertising
Facebook Ads
Analyze campaign-level Facebook Ads reporting with imported daily snapshots.
Assisted rollout · read onlyAccounting
Tally
Import groups, ledgers, stock items, and date-bounded vouchers through your local connector.
Imported snapshotPrivate network
Private connector
Reach approved databases inside your network through an outbound TLS connection.
Assisted setupNo connectors match your search. Try a database name or another category.
Live, not a snapshot
Connected data beats a one-time upload.
Uploading a file gives you an answer about the data as it was the moment you exported it. Connecting the source gives you an answer about the data as it is right now — every time you ask.
| Capability | One-time file upload | Connected in tableArth.ai |
|---|---|---|
| Data freshness | Frozen at export time | Live — reflects the source |
| Keeping it current | Re-upload every change | Refresh behavior depends on source |
| Multiple tabs / tables | Flatten into one sheet | Understood & joinable |
| Join across sources | Not possible | Ask across all of them |
| Large datasets | Upload timeouts | Reliable, streamed loads |
| Private databases | Export required | Query in place, in your env |
Workbook
One place. Every source. All in context.
A Workbook keeps related sources, questions, charts, and dashboards together. Source type determines whether analysis uses live queries or an imported snapshot. Configure relationships where supported and review the source status before analyzing updates.
- Multiple sources — Sheets, Excel, MySQL, MongoDB, and more, side by side
- Source-specific freshness — live database queries, refreshed snapshots, and updated imports
- Unified answers — one question, pulled across every connected source
Sales pipelineGoogle Sheets
OrdersMySQL
EventsMongoDB
Workbook
Synced
Sales pipeline ✓ live
Orders ✓ live
Events ✓ live
Multiple sheets & tables
Your data doesn't have to live in one flat sheet.
tableArth.ai understands workbooks with many tabs and databases with many tables. Ask questions across them and join related data — the same way you would across database tables — with no manual VLOOKUPs, no copy-paste, no combining first.
Reads every tab
Multi-tab Sheets and Excel workbooks are read as related tables, not one blob. Each tab keeps its own columns and types.
Joins related data
Ask a question that spans tabs or tables and tableArth.ai works out how they relate, joining on shared keys automatically.
Answers in context
Get a single answer and the right chart, drawn from whichever tabs and tables the question actually needed.
Talk to your database
Ask your private databases, in plain English.
Query external databases such as PostgreSQL, MySQL, MongoDB, and Druid running inside your own private environment — simply by asking. No exports, no copies leaving your network. The question is natural language; the answer is grounded in a real query run against your data.
- Runs where your data lives — nothing has to move
- SQL and NoSQL — relational tables or MongoDB collections
- Four privacy modes control exactly what a model can see
PostgreSQL · orders
AskQuery
You
Which customers churned last month but had > $10k lifetime value?
18 customers churned in June with lifetime
value above $10k — together $41.2k
of monthly recurring revenue. Top three: Northwind, Contoso, Globex.
SELECT c.name, c.ltv FROM customers c
JOIN churn e ON e.customer_id = c.id
WHERE e.month = '2026-06' AND c.ltv > 10000;
JOIN churn e ON e.customer_id = c.id
WHERE e.month = '2026-06' AND c.ltv > 10000;
How it works
Connect. Sync. Ask.
Three steps from a source to an answer — no warehouse, no data prep, no SQL.
Step 01 — Connect
Pick a source
Authorize a Google Sheet, connect an Excel file, or point tableArth.ai at a database. Upload a CSV if you'd rather. The engine reads the structure automatically.
Sheets · Excel · Databases
Step 02 — Sync
Build a Workbook
Add selected sources to a workbook. Check their status before analysis: databases query on demand, connector snapshots need refresh, and imported files need updated data.
Auto-sync, multi-source
Step 03 — Ask
Ask in plain English
Type a question. tableArth.ai figures out which sources and tables it needs, joins them, runs the query, and answers with the right chart — with suggested and clarifying questions along the way.
Answers + charts
Guided, not guesswork
It suggests questions — and asks when you're vague.
Smart suggestions
tableArth.ai suggests relevant questions for your data so you always have a strong starting point — no blank box, no guessing what's answerable.
Revenue by region
Top accounts this quarter
Month-over-month growth
Churn by plan
Clarifying questions
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.
You: best customers?
tableArth.ai: By revenue, retention, or lifetime value?
tableArth.ai: By revenue, retention, or lifetime value?
Also from tableArth.ai
Building software? Embed the same engine.
The engine that answers your questions also drops into your own product. Give your customers plain-English analytics on their tables with a two-line widget, a REST API, or a Chrome extension — the same natural-language answers, charts, and privacy modes.
FAQ
Connecting your data.
What data sources can I connect?
Connect Google Sheets, Excel and CSV files, nine database engines, cloud billing exports, supported ad reports, and Tally imports. Setup and availability vary by connector. Databases support on-demand queries; snapshot sources require refresh or a new import.
Is my data live, or a one-time upload?
Refresh behavior depends on the connector. Databases query selected data on demand. Google Sheets, cloud billing, and advertising use refreshed snapshots; uploaded Excel, CSV, and Tally data stays at the imported version until updated.
Can I ask questions across multiple sheets or tables?
Yes. tableArth.ai understands files with multiple tables or tabs across Google Sheets, Excel, and databases. You can ask questions across sheets and join related data the same way you would across database tables — your data no longer needs to be combined into one flat sheet first.
Can it answer one question across several sources at once?
Yes. With a multi-source Workbook, you ask a question in natural language and tableArth.ai pulls data across all your connected sources to return a single, unified answer. See how Workbook works.
Do I have to move my database?
No. You can query external databases such as PostgreSQL, MySQL, MongoDB, and Druid running inside your own private environment, simply by asking. Your data stays where it lives. Read more on the talk-to-your-database and security pages.
What about large files?
Large uploads are handled reliably — the timeout issues that used to affect bigger datasets are fixed, so the upload process is smoother for large files.
Get started
Connect a source. Ask your first question.
Start with one sheet or one database. Connect it, ask in plain English, and see an answer and a chart in seconds.
AI native by design · MCP previewYour data.
Your data.
Your AI workspace.
Keep the conversation where you work. MCP brings authorized tableArth workbooks into compatible clients such as Claude, ChatGPT, and Cursor.
From Tally and spreadsheets to databases, cloud bills, and ad reports: connect the source once, then explore its workbook context through the tools you choose.
Ask your dataExplore dashboardsCreate new views
Explore MCP access Staged preview. Availability depends on your client, deployment, and plan. Creating or updating dashboards requires write permission.
One workbook. More ways to work.MCP
Your connected dataOne authorized workbook
Imagine asking in ClaudeExample
“Explore my workbook, explain what changed, and help me build a dashboard for the next review.”
Workbook context → governed analysis → a dashboard you can return to.