PDFs in. Clean, checked Excel out.
I convert clear PDF tables into an analysis-ready Excel/CSV file — with typed fields, source-page traceability, validation checks and every uncertainty flagged instead of guessed.
Send a sample PDFSee the finished outputFixed scope from €129 · target turnaround 24h · one correction round included
Not transcription. A file you can actually use.
Columns mapped to one agreed schema. Dates, numbers and text are normalized rather than dumped as raw OCR.
Each extracted row can carry its source page so a value can be checked against the original PDF quickly.
Missing, ambiguous or conflicting values are flagged in a QA log. Uncertainty is never silently invented.
- Required-field and duplicate checks
- Datatype and formatting normalization
- Source-page traceability
- Discrepancy / exception report
- CSV or Excel-ready output
What the finished output looks like
The example below shows the difference between simple extraction and validated delivery: one row is intentionally flagged because the source is ambiguous.
| record_id | invoice_date | supplier | amount_eur | source_page | validation_status |
|---|---|---|---|---|---|
| INV-1042 | 2026-08-12 | Northline Supplies | 842.50 | 2 | OK |
| INV-1043 | 2026-08-13 | Delta Components | 1290.00 | 4 | OK |
| INV-1044 | 2026-08-14 | Meridian Parts | — | 5 | REVIEW REQUIRED |
Simple scope. Clear boundary.
€129
For a first bounded job with up to 30 clear PDF pages and one agreed target schema.
- Extraction + normalization
- Validation checks
- Source-page traceability
- Exception / discrepancy log
- One correction round for in-scope mapping errors
- Target delivery within 24 hours after scope confirmation
Larger batches, irregular tables or multiple schemas are quoted separately before work starts. No surprise expansion after the file arrives.
Before you send a file
Why not just use OCR or ChatGPT?
Those can extract text quickly. The paid part here is the checking layer: agreed schema, normalized datatypes, cross-row consistency, source traceability and a visible exception list instead of silent guesses.
What documents fit the fixed €129 scope?
Clear digital PDFs or clean scans with regular tables, up to 30 pages, one target schema and no handwriting or complex nested layouts.
Do you need confidential data?
No. Send only what is necessary for the task. For sensitive or regulated data, agree handling requirements before sharing files. The public sample uses fictional data only.
What if a value cannot be read reliably?
It is flagged for review. Ambiguity is not guessed or silently filled.
Can this become a recurring workflow?
Yes, but only after the manual proof is correct. Repeating supplier or reporting PDFs can then be assessed for a reusable extraction/validation pipeline.
Have a PDF table that needs to become usable data?
Send one representative sample and the columns you need. I’ll confirm whether it fits the fixed scope before any work starts.
hello@nexaproject.be