Excel2Insight Guide — Analyze Excel Data with AI

Excel2Insight is a service that automatically analyzes your uploaded Excel files and generates visual insight reports using AI.

Getting Started

Log in with your GRAXEL account and find Excel2Insight in the service catalog. The free plan allows up to 10 analyses per month, while the premium plan offers unlimited access.

Uploading Excel Files

Supported formats include .xlsx, .xls, and .csv, with up to 50MB / 1 million rows. Simply drag and drop to upload, and AI immediately identifies the data structure.

Viewing AI Analysis Results

Results are provided as charts, tables, and text summaries, downloadable as PDF or PowerPoint. Analysis typically takes 30 seconds to 2 minutes.

Tips

For more accurate analysis, include header rows and minimize empty cells. YYYY-MM-DD date format is recommended. If results aren't satisfactory, you can enter custom prompts for specific analysis perspectives.

How this connects to the live GRAXEL portal

This guide is part of the same operating model described on the About GRAXEL page and the platform overview. The goal is not to publish generic AI copy, but to document how a real service portfolio is planned, shipped, measured, and improved.

For implementation work, GRAXEL follows official framework guidance instead of treating examples as copy-paste snippets. The portal uses patterns documented by Next.js and localization practices aligned with next-intl. If you want to ask about this workflow or suggest a service improvement, use the contact page.

Practical takeaway

• Start with one narrow user problem before adding more automation.
• Keep source data, user-facing explanation, and billing assumptions separate.
• Review the page in a real browser before assuming search engines or ad reviewers will understand it.

Preparing a spreadsheet before analysis

Excel analysis works best when the spreadsheet has a predictable shape. Before uploading or processing a file, I check whether the first row contains clear column names, whether dates use a consistent format, and whether sensitive fields are necessary for the question. A sheet full of merged cells, hidden formulas, and mixed units can produce misleading summaries even when the AI layer is working correctly.

For privacy, I recommend removing names, phone numbers, resident registration numbers, raw emails, and internal notes unless the analysis specifically requires them and the environment is approved. A safer workflow is to create a copy of the file, keep only the columns needed for the question, and document what was removed. Then ask focused questions: revenue by month, missing values by column, unusual outliers, or category totals. The output should be treated as an analysis draft, not a final accounting record. Users should verify formulas, totals, and assumptions before making business decisions. Excel2Insight is most useful when it turns a messy sheet into a reviewable checklist.

Extra review step

When the analysis result looks surprising, I trace it back to the source rows before trusting the insight. Many spreadsheet “AI mistakes” are really data-shape problems: duplicated headers, totals mixed with raw rows, hidden filters, or inconsistent currency columns. The tool should help find those problems, but the user should still confirm the final business meaning.