What

Luminal is an AI copilot for spreadsheets that helps users clean, transform, analyze, and visualize data through natural-language prompts. It is positioned as a simpler alternative to manually working in Excel, writing formulas, or building scripts for common spreadsheet operations.

The product appears suited for professionals and general users who work with messy or large spreadsheet files and want faster handling of tasks such as reformatting, categorization, calculations, and quick analysis. Its core workflow is straightforward: upload a spreadsheet, submit a prompt, and review the AI’s output along with an explanation of the actions performed.

Features

Natural-language spreadsheet operations — Users can request cleaning, formatting, calculations, analysis, and other edits without writing formulas or code.
Spreadsheet file upload support — Luminal accepts .csv, .xlsx, .xls, and .xlsm files, which helps teams work with common spreadsheet formats.
Large dataset handling — The site states support for spreadsheets with tens of thousands of rows and references cleaning datasets up to one million rows.
AI-generated answers with action explanations — After a request, the system returns results along with a description of what it changed, which can support transparency and review.
Data visualization creation — Users can instruct the AI to generate graphs, charts, or maps from spreadsheet data.
Multilingual interaction and security controls — Luminal supports prompts in multiple languages and states that data is hosted with US/EU cloud providers and encrypted in transit and at rest.

Helpful Tips

Validate outputs on sensitive workflows — For financial, operational, or regulatory reporting use cases, review AI-made transformations carefully before relying on them downstream.
Start with high-friction spreadsheet tasks — This kind of product is most useful where teams repeatedly clean columns, standardize formats, categorize records, or answer recurring data questions.
Test with representative file sizes and complexity — If your spreadsheets include very large row counts, formulas, mixed data quality, or multiple tabs, confirm performance and output quality on real samples.
Define prompt patterns for repeated tasks — Standardized internal prompts can improve consistency when different team members use AI for cleaning and analysis.
Check plan limits against usage volume — The site lists interaction-based pricing tiers, so adoption planning should account for how often teams will submit requests.