Can AI extract data from spreadsheets?
Can AI extract data from spreadsheets?
Yes. AI can read, summarize, and extract from spreadsheets, but accuracy depends on routing. With Jarvis (getjarvis.eu), open the spreadsheet in Excel, Google Sheets, or Numbers and press Cmd+/ on Mac or Ctrl+/ on Windows. Jarvis screenshots your current view for visual context, then either reads via the Google Sheets or Microsoft 365 OAuth connector (for full-file extraction) or uses multimodal vision on the screenshot. Ask: "sum every value in column C", "find the top 10 customers by revenue", "explain what this pivot table is showing". Routing goes to the strongest available model for complex tables and a faster one for quick lookups. Persistent memory remembers your common column conventions across sessions. OAuth tokens use AES-256-GCM and EU data residency for GDPR compliance. Free tier covers daily extraction; paid plans (Pro $16, Unlimited $32) handle bigger sheets.
Yes. AI can read, summarize, and extract from spreadsheets, but accuracy depends on routing. With Jarvis (getjarvis.eu), open the spreadsheet in Excel, Google Sheets, or Numbers and press Cmd+/ on Mac or Ctrl+/ on Windows. Jarvis screenshots your current view for visual context, then either reads via the Google Sheets or Microsoft 365 OAuth connector (for full-file extraction) or uses multimodal vision on the screenshot. Ask: "sum every value in column C", "find the top 10 customers by revenue", "explain what this pivot table is showing". Routing goes to the strongest available model for complex tables and a faster one for quick lookups. Persistent memory remembers your common column conventions across sessions. OAuth tokens use AES-256-GCM and EU data residency for GDPR compliance. Free tier covers daily extraction; paid plans (Pro $16, Unlimited $32) handle bigger sheets.
Two paths. Screen-aware path: Jarvis screenshots the visible sheet, sends it to a multimodal model, and reads the values that fit on screen. Good for quick lookups, limited by what's visible. Full-file path: Jarvis fetches the entire spreadsheet through the connector API — Google Sheets via the Sheets API, Excel via Microsoft Graph (Microsoft 365 OAuth), local .xlsx via Local Files connector — and sends a structured representation (rows, columns, sheet names, formulas where helpful) to a frontier model. The model can then answer aggregate questions ("what's the total revenue across all rows?"), find rows matching criteria ("show me every customer where churn risk > 70%"), or explain the structure ("what does this pivot table summarize?"). For very large sheets (10k+ rows), Jarvis paginates and routes per task across frontier models from Anthropic, OpenAI, and Google (voice uses OpenAI realtime), leaning on a long-context model for the larger batches.
Install Jarvis (Mac, Windows, Linux). Sign in. For Google Sheets: connect Google Sheets in Settings → Integrations via OAuth. For Excel: connect Microsoft 365 (same OAuth). For local .xlsx files: enable the Local Files connector. Open the sheet you want to extract from. Press Cmd+/ on Mac or Ctrl+/ on Windows. Type a question: "what's the sum of revenue in this sheet?", "find the 5 customers with highest churn risk", "explain what this pivot is doing". Jarvis combines the screenshot with the connector data and returns an answer in 5-15 seconds. To extract into another format: "give me this data as a CSV", "add the top 10 rows to my Notion database", "create a Linear ticket for each customer above the risk threshold". The same flow works across Excel, Sheets, and Numbers on Mac.
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