Batch Document to Excel: One Sheet for the Whole Folder
A folder of 200 documents is roughly 10 hours of typing by hand. Upload the batch at once, name the columns you want once, and every file comes back as rows in one Excel spreadsheet, with its source file name kept on each row.
5-10s per document · Whole batch in one upload · One merged spreadsheet
What You Can Extract from Any Batch of Documents
Getting through a folder of documents shouldn't mean opening them one by one. Name the columns you need, such as Date, Amount, Vendor, and Line Items, and every file in the batch comes back in a single spreadsheet, with the same headers all the way down.
Type these as column names, or define your own. What you type becomes the header of each column in the output spreadsheet, and every document in the batch is read against those same columns.
One Spreadsheet to Finish, Not 200 Files to Open
The hard part of a big batch isn't reading any single document. It's the repetition: the same handful of fields, pulled out of hundreds of files and then stitched into one sheet by hand. At that scale, doing it yourself is the bottleneck, and so is a tool that hands back one output file per input.
Why Doing It by Hand Doesn't Scale
Typing time grows with the folder. A stack of 200 documents is roughly 10 hours of manual entry at about 3 minutes each. A 400-document folder is 20 hours, and almost none of that time is thinking work. Double the volume and you double the hours, which is why big batches are the ones that never seem to get done.
One-file-at-a-time tools leave you with a pile of outputs. A standard PDF-to-Excel converter gives you 200 spreadsheets, one per document, each with its own column layout. The real work starts after that: merging them, matching headers, and fixing dates and amounts that were copied exactly as they were printed.
At volume, one bad row is easy to miss. In a sheet with hundreds of rows, a misread amount or a missing field can sit unnoticed for weeks. If rows aren't tied back to the file they came from, checking means opening documents one at a time until you find the right one.
How the Whole Batch Comes Back as One Sheet
The whole folder goes in as one batch. Upload every file at once, PDFs, scans, and photos together. Each document is read against the columns you named, so the headers stay identical from the first row to the last, and you review one sheet instead of a folder of finished files.
Every row keeps its source file name. Batch exports add a File Name column, so each row carries the document it came from. Sort by it, filter by it, or hand the sheet to someone else for review and they can trace any line back to the page it was read from.
One weak file doesn't undo the batch. Documents are processed independently, each with its own status. A faded scan on one row doesn't stop the other 199 from finishing, and you can correct that row on its own without re-running the rest.
How Batch Document to Excel Works in Practice
Here's the whole job in three steps, using a folder of 40 documents that would otherwise take about two hours of typing.
Upload Everything in One Batch
Your folder has 40 files: 25 PDF invoices from different ERP systems, 10 scanned invoices as JPGs, and 5 mobile photos of handwritten receipts. Drag them all into the upload area. The tool accepts PDF, JPG, PNG, WebP, AVIF, Word, and text files, so there's no format pre-sorting and no separate batches for scans versus digital PDFs. Each file can be up to 10 MB.
Define Your Columns Once
Type Invoice Number, Date, Vendor, Subtotal, Tax Amount, Total, Due Date. These names become the headers of your output spreadsheet. Optionally add a computed column like Line Total (Qty × Unit Price), and the AI performs this calculation during extraction for every document in the batch, even when each document has a different number of line items.
Download One Merged Spreadsheet
Processing takes 5-10 seconds per document. The output is a single XLSX or CSV file, and every document contributes rows with matching column headers. A PDF from supplier A, a scan from supplier B, and a phone photo from supplier C all land in one table with the columns you defined, and each row keeps its file name for tracing. That is roughly 18x faster than manual entry (about 3 minutes of typing per document versus 5-10 seconds here).
When Batch Extraction Works, and When to Be Cautious
Batch document extraction isn't a magic button. Understanding its limits helps you use it well and know when a folder needs splitting or a second look.
When It Works Best
A large folder with the same few fields on every document. When you need Invoice Number, Date, and Total from 200 invoices, the columns stay the same from the first row to the last. This is the job batch extraction is built for.
Printed text with clear field labels. Up to 99% accuracy for printed text when labels are present. If your documents consistently show "Date:", "Total:", or "Due Date:" near the corresponding values, the AI identifies them reliably regardless of page position.
Batches that scale with your plan. Batch size depends on your plan: from 20 pages on the free tier up to 500 per batch on the top plans (10 MB per file). Larger folders split into multiple runs, and each run produces its own merged spreadsheet that you can combine afterward.
When to Be Cautious
Low-resolution scans or heavily compressed images. Faded print, poor contrast, or aggressive JPEG compression reduces accuracy. The visual LLM still outperforms traditional OCR by using surrounding context, but you should expect to review results. Scanning at 300 DPI or higher produces the best output.
Dense handwriting or cursive text. The tool handles neat printed handwriting reasonably well. Heavy cursive, dense annotation, or faint pencil markings will reduce accuracy and require manual review. If your batch includes a mix of printed and handwritten documents, the printed ones will extract more reliably.
Labels that rely purely on spatial layout with no text. If a document shows a value (e.g. "$1,250") without any nearby label like "Total" or "Amount", the AI cannot reliably determine what that value represents based on position alone. Fields that are labeled, even inconsistently across documents, extract much more accurately than purely positional data.
Frequently Asked Questions
Can I process a whole folder of documents in one batch and get a single Excel file?
Yes, up to your plan's batch limit. Drag the folder in as one batch: PDFs, JPGs, PNGs, WebP, and AVIF files together. The AI extracts the columns you named from every document, and the output is one spreadsheet with the same headers all the way down. If the folder is larger than one batch, split it into a few runs, and each run produces its own merged sheet that you can combine afterward.
How do I tell which row in the spreadsheet came from which document?
Batch exports add a File Name column, so every row carries the name of the document it was extracted from. You can sort, filter, or audit the sheet by source file. During processing, each document also has its own status, so it's easy to spot the one row that needs a second look without reopening the rest of the batch.
How does this handle documents with different numbers of line items, from 1 row on one document to 50 on another?
Each document generates as many output rows as it has line items. A single-line invoice produces one row with the header fields and one line item row. A 50-line purchase order produces 50 rows, all sharing the same column headers (Quantity, Unit Price, Line Total, and so on) in the output spreadsheet. You don't pre-define row counts, and you don't get a broken table because the input lengths vary. The AI reads each document's structure and expands the output to match.
Can I include calculated columns in a batch extraction, for example Line Total computed as Qty × Unit Price?
Yes. Computed Columns let you define calculations that the AI performs during extraction rather than afterward in Excel. Type "Line Total (Qty × Unit Price)" as a column name, and the AI multiplies the values it finds for Quantity and Unit Price on each document, outputting the result directly. This works across every document in the batch, even when one document has 1 line item and another has 50. You can also use Rule Format (available to logged-in users) for more complex multi-step calculations such as cross-row aggregation or conditional logic.
What happens when one document in the batch is poor quality? Does the whole batch fail?
No. Each document is processed independently. If one file in a batch of 200 is a faded scan with low contrast, that document's extraction accuracy will be lower, but the other 199 files are unaffected. The poor-quality document still appears in the output spreadsheet with whatever values the AI was able to extract. You can review and correct that row without re-running the entire batch. For best results, scan documents at 300 DPI or higher, use direct captures rather than re-screenshots, and split very large folders into batches that match your plan limit.
Read more: batch data extraction for large document sets · mixing different document types in one spreadsheet · 40 Invoices, One Spreadsheet: Batch Extract Invoice Data Without Copy-Pasting · Why Document Collection and Data Extraction Should Be One Workflow · How to Get Clean, Accurate Output from AI Document Extraction