Label invoices in seconds

Invoice labeling annotates invoices and related financial documents with structured labels that ML models use as training data. Each region of the document is tagged with its semantic role (vendor, line item, quantity, unit price, tax, total, due date) and exported in a format your pipeline can consume directly.

Vendor invoices, receipts, purchase orders, credit notes and refunds, utility and recurring bills, and multi-page or batch invoices from any layout or template.

Labels are typically 92%+ accurate on standard invoice layouts. Confidence scores attach to every label so low-confidence fields can be flagged for manual review before training runs.

Structured JSON with bounding boxes, segment text, label classifications, and confidence scores. Markdown is also supported. Both are directly compatible with PyTorch DataLoaders, TensorFlow Datasets, and Hugging Face Transformers.

Yes. Label your first 5 pages without an account. Larger batches and API access are available on paid plans.

Yes. Documents are processed over encrypted connections, never used for model training without explicit consent, and can be deleted immediately after labeling. Enterprise plans include SOC 2 compliance and private deployment options.