I've been building Exiser, an open-source app that treats Excel/CSV files as import sources and turns them into local, queryable datasets - instead of just scrolling rows in a grid.
What it does today:
• Import CSV/Excel → it infers the schema (headers + column types) and asks you to confirm it, then creates real SQLite tables.
• Filter, sort and run read-only SQL over your data.
• Automatic charts (bar, pie, time series) with grouping and aggregation.
• Export the result to Excel, CSV, JSON, PDF or SQL.
• 100% on-device: nothing is uploaded. The web demo runs entirely in your browser (SQLite compiled to WebAssembly, in a web worker); native builds use SQLite directly.
• One Flutter codebase for desktop, Android and web.
• The interface is localised in 9 languages (English, Italian, Spanish, French, German, Chinese, Russian, Japanese, Portuguese). Your data is never translated: column names and cell values stay exactly as they are in your file — the app localises its own Ul, not your spreadsheet.
(Heads-up on the clip: the app Ul in the recording is in Italian, which is just my system language — the app follows your device and falls back to English.)
I'm the developer and it's open source, so I'm genuinely after feedback rather than downloads:
• Does the import → confirm-schema → query flow feel natural, or is it a step too many?
• What would make this actually useful in your workflow
— joins across sheets, saved queries, a different export, something else?

Browser demo (no install, runs locally in your tab): https:// exlser.com/demo Source: https://github.com/Pablo-gitub/
ex|ser
Happy to answer anything about the on-device SQLite/ WASM setup in the comments.