nolainocr

What is nolainocr?

nolainocr is an AI-powered OCR tool that extracts structured data from PDF documents such as invoices, receipts, forms, and contracts. The goal is to turn the information inside your documents into usable outputs so you can avoid manually typing data into spreadsheets or databases.

After you upload a PDF, nolainocr generates structured results that you can export as Excel, Google Sheets, or JSON. It’s designed for batch processing—such as multiple invoices packed into a single PDF—and it uses the document layout to extract fields consistently across pages.

Key Features

PDF-to-structured-data extraction for invoices, receipts, forms, and contracts: Upload document files and convert them into structured outputs.
Excel, Google Sheets, and JSON outputs: Export extracted fields in formats useful for spreadsheet work or downstream processing.
Batch processing of multi-page PDFs: Upload one PDF containing multiple invoices/receipts/forms and extract from all pages.
Extraction configuration options: Set how many pages correspond to each document (e.g., pages per receipt/invoice/form) and choose an extraction mode.
Extraction modes with or without project history: Options include a mode that does not keep a record of extracted data, and project-based modes that add results to a project or update an existing one.
Column selection and result preview: Review extracted text and choose which columns to include (e.g., supplier, bill-to, invoice number, totals, and line-item fields).

How to Use nolainocr

Upload your PDF (the source content indicates the supported input type is PDF).
If your PDF contains multiple documents, ensure they match the same layout so extraction stays accurate.
Configure extraction settings, such as pages per receipt/invoice/form and the extraction mode you want.
Run extraction and review the results in the on-page preview.
Select columns and export the extracted data to Excel, Google Sheets, or JSON.

If your documents have different layouts, group them into separate PDFs by layout type and process each group separately.

Use Cases

Bookkeeping from expense receipts in bulk: Upload a single PDF with many receipts (same layout) and extract fields such as receipt number, vendor, date, category, subtotal, tax, and totals.
Accountants consolidating many invoices: Provide one PDF containing multiple invoices/receipts/forms and generate a single structured spreadsheet output for easier reconciliation.
Real estate document auditing: Process lease agreements from a combined PDF (same template/layout) to extract lease-related fields like property identifiers, landlord/tenant information, monthly rent, and lease term dates.
Claims and forms data entry support: Convert a week’s worth of claim forms into structured entries by extracting repeated fields from documents that share the same form layout.
Line-item extraction for invoices: For invoices that include items, extract quantity, unit price, and line totals, then export the result into a spreadsheet with selected item-related columns.

FAQ

Does nolainocr support file types other than PDF?

The page content only states that the supported file type is PDF. If you need support for other formats, you may want to confirm before uploading.

What happens if my uploaded PDF contains invoices/receipts with different layouts?

The workflow described is to group documents by layout type (make one PDF per group) and run extraction separately for each group to keep processing accurate.

Can I upload one PDF that contains multiple documents?

Yes. The page describes uploading one PDF containing multiple invoices, receipts, or forms, then extracting from all pages.

What output formats are available?

The page lists export options as Excel, Google Sheets, and JSON.

Can I review and choose which fields go into the output?

Yes. The interface includes a result preview where you can view extracted text and select columns such as supplier, bill-to, addresses, invoice/date, and totals (plus line-item fields where present).

Alternatives

Generic OCR tools that export to spreadsheets: These may handle text recognition, but the workflow may require more manual mapping to structured columns compared with a purpose-built invoice/receipt/form extraction process.
Spreadsheet-based import workflows using template matching: You can build a process that extracts fields using document templates and scripts, but it may involve more setup and maintenance than a one-upload extraction workflow.
Other document-to-data extraction platforms: Instead of OCR-only, other tools in this category focus on converting structured fields from documents into spreadsheets or JSON; differences typically come from how they handle layout consistency, grouping, and field configuration.
Manual data entry with spreadsheet templates: For very small volumes or highly variable document layouts, a manual workflow can be simpler, though it doesn’t reduce typing effort and time in the way automated extraction does.