Expense AI · New

Label expenses in seconds

Upload expense reports, receipts, and reimbursement forms. Get ML-ready labels with categories, amounts, and dates structured for your AI pipeline.

Try Free → See how it works

No signup · First 5 pages free · JSON / Markdown export

How it works

Three steps to labeled data

From raw PDF to training-ready dataset in under a minute.

Upload

Drop any expense PDF — scanned or native. Expense reports, receipts, reimbursement forms, per diem claims, anything.

Auto-label

AI detects categories, amounts, dates, merchants, and payment methods using an expense-trained taxonomy.

Export

Download as JSON or Markdown. Feeds directly into PyTorch, TensorFlow, or Hugging Face.

Document types

Built for every expense format

Domain-trained models for the expense documents your team actually works with.

📋

Corporate Expense Reports

Categories, amounts, dates, project codes, and approval status extracted from any template.

🧾

Itemized Receipts

Merchant, date, individual line items, tax, tip, and payment method identified automatically.

📝

Reimbursement Forms

Employee details, claim amounts, expense categories, and supporting receipt references structured cleanly.

🍽

Per Diem & Meal Claims

Daily rates, travel dates, location, and meal breakdowns labeled per your organization's policy structure.

🚗

Mileage & Travel Logs

Trip dates, origin and destination, distance, purpose, and reimbursement rates extracted line by line.

✈️

Travel Expense Summaries

Flights, hotels, ground transport, and incidentals broken down by trip and cost category.

FAQ

Questions, answered

Everything you need to know before you start.

What is expense labeling?

Expense labeling annotates expense documents with structured labels that ML models use as training data. Each region of the document is tagged with its semantic role (category, amount, date, merchant, payment method, project code) and exported in a format your pipeline can consume directly.

Which expense document types are supported?

Corporate expense reports, itemized receipts, reimbursement forms, per diem and meal claims, mileage and travel logs, and travel expense summaries from any layout or template.

How accurate is automated expense labeling?

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

What export formats are supported?

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.

Is the tool free?

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

Is my expense data secure and confidential?

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.

Label expenses in seconds

Three steps to labeled data

Upload

Auto-label

Export

Built for every expense format

Corporate Expense Reports

Itemized Receipts

Reimbursement Forms

Per Diem & Meal Claims

Mileage & Travel Logs

Travel Expense Summaries

Drop straight into your stack

Start labeling now

Questions, answered

Explore the platform

Label expenses in seconds

Three steps to labeled data

Upload

Auto-label

Export

Built for every expense format

Corporate Expense Reports

Itemized Receipts

Reimbursement Forms

Per Diem & Meal Claims

Mileage & Travel Logs

Travel Expense Summaries

Drop straight into your stack

Start labeling now

Questions, answered

Explore the platform

General Data Labeling →

Invoice Labeling →

Platform →