Use Case · Expense Platforms

Stop fake receipts before they're reimbursed

Expense fraud costs businesses 5% of annual revenue on average. Hesper AI intercepts forged and manipulated receipts before your OCR pipeline reads them.

The problem with receipt validation today

Most expense platforms validate receipts by extracting text with OCR and checking whether the amount, date, and vendor look plausible. But OCR reads what the document says — it can't tell whether the amounts were edited after the fact. A receipt with a digitally altered total of $1,847 looks identical to a legitimate one. AI image editing has made this trivial to execute, and nearly impossible to catch manually.

of annual revenue lost to expense fraud on average

$47K

average fraudulent claims found per customer in first 90 days

73%

of expense fraud goes undetected with OCR-only validation

How to integrate with your expense platform

Hesper AI slots directly into your receipt submission flow. You add one API call before your existing OCR step — no changes to your UI, database schema, or downstream processing.

User submits receipt

Your existing upload flow captures the receipt image or PDF.

POST to /v1/analyze before OCR

Before passing to your OCR pipeline, send the raw file to Hesper AI. We return a verdict in under 80ms.

Route based on fraud score

Score above your threshold? Send to manual review queue. Score below? Continue to your existing OCR and approval flow.

Explainable findings for reviewers

For flagged receipts, Hesper AI returns the specific regions and reasons — so your reviewers can make a fast, informed decision.

The ROI is immediate

Companies typically see Hesper AI pay for itself within the first month of deployment through recovered fraudulent claim value alone. For a company processing 5,000 expense reports per month, the break-even is typically catching fewer than 3 fraudulent claims per month on the Enterprise plan.