Data Extraction (OCR & Structured)

Turn unstructured documents into myDATA-ready data — automatically.

🧠 How TaxLayer Extracts Your Data

Once you upload a file, TaxLayer goes to work:

  • OCR reads PDFs and images (Greek + English supported).

  • AI interprets content into structured fields (VAT, totals, dates, parties, line items).

  • Confidence scoring flags uncertain extractions so you know what needs a manual check.

💡 Why it matters: No more manual typing or copy-pasting invoice data. Clean extraction means fewer myDATA rejections, faster validation, and a smoother submission process.


🪄 OCR Capabilities That Match Greek Business Reality

  • Greek + English support: Handles ΑΦΜ, Ημερομηνία, ΦΠΑ just as easily as “VAT” and “Invoice Date.”

  • PDFs, JPGs, PNGs: Both scanned and native documents work.

  • Smart correction: Fixes orientation, recognises multi-page docs, and optimises resolution.

💡 Why it matters: Most Greek invoices mix languages and formats. Our OCR is tuned for that complexity, so critical fields don’t get lost.


📋 Best Practices for Clean Extraction

For best results:

  • Scan at 300 DPI or higher (low quality scans = low confidence scores).

  • Keep documents upright (avoid sideways photos).

  • Avoid glare and shadows in mobile photos.

  • Keep files under 10MB for faster processing.


🗂️ What Gets Extracted

TaxLayer pulls out everything myDATA needs:

  • Headers & IDs: Invoice number, type, series, dates.

  • Amounts: Net, VAT, gross totals, currency detection, rounding checks.

  • Parties: Issuer + recipient VAT, name, address, country.

  • Line items: Descriptions, quantities, units, prices, discounts, VAT categories.

  • myDATA fields: Auto-suggests document types (1.1, 1.2, etc.) and classification codes.

💡 Why it matters: Getting these right up front prevents downstream schema errors and AADE rejections.


📊 Confidence Scoring Explained

Every field is graded for reliability:

  • High (90–100%) → Safe to auto-accept.

  • ⚠️ Medium (70–89%) → Worth a quick check.

  • Low (<70%) → Needs manual review.

Factors that affect confidence: image clarity, text quality, document structure, language mix.

🔎 Smart workflow: High-confidence fields flow through automatically, while medium/low confidence ones are queued for review — saving time without sacrificing accuracy.


🧩 Smarter Matching with Context

Extraction isn’t just text recognition — TaxLayer also:

  • Matches VAT numbers against EU databases.

  • Links issuers/recipients to existing client/vendor records.

  • Suggests myDATA classifications based on history.

  • Flags odd values (e.g. €10,000 invoice from a small vendor).

💡 Why it matters: You don’t just get raw data — you get data enriched and pre-checked for compliance.


🛠️ When Extraction Needs a Human Touch

Even the best OCR has limits. Issues arise with:

  • Blurry scans or faxed copies.

  • Custom invoice layouts.

  • Mixed Greek/English fields with unusual terminology.

  • Totals that don’t add up.

Quick fixes:

  • Correct inline in the Document Detail view.

  • Use XLSX/CSV uploads for bulk structured data.

  • Re-scan documents at higher quality.

  • Let TaxLayer “learn” — every correction trains the system to get smarter next time.


🎯 Pro Tips for Maximum Accuracy

  • Work with vendors to standardise invoice layouts where possible.

  • Use structured formats (XLSX/CSV) when you have bulk data.

  • Correct consistently (same error, same fix) so the AI learns faster.

  • Update client/vendor records regularly — accurate VATs and addresses improve matching.


  • Validation & Quality Control – What happens after extraction.

  • Batch Processing – Organize and monitor uploads.

  • Knowledge Management – Train the system on your company rules.

  • AI Chat – Ask “What fields are missing?” or “How do I fix these VAT mismatches?” for instant guidance.

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