Extract credit note data with AI — credit note number, original invoice, amount, reason — from PDFs, scans and photos. Straight to Excel, CSV, JSON or your systems via API. No templates, no manual entry.
Upload a document to extract
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Up to 50 files
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Upload a credit note and see the extraction live, free, no signup required.
Every field captured automatically, validated, and exported in a clean structure, regardless of layout or vendor.
Drop in a PDF, scan or photo, single file or a batch of thousands.
Our models read every field and table, validate them, and flag anything that needs review.
Download Excel, CSV or JSON, or push structured data into your systems via API.
One-click export, or connect LenderAnalyzer to the tools your team already uses.
Common questions about extracting credit note data with AI.
Credit Note OCR uses AI to read a Credit Note document, whether a PDF, scan or photo, and extract structured data such as credit note number, original invoice, amount, reason into Excel, CSV, JSON or your systems via API.
Yes. LenderAnalyzer combines OCR with machine-learning models trained on millions of documents, so it reads scanned, photographed and native-PDF Credit Note files accurately, with no template setup required.
LenderAnalyzer captures the key fields, including credit note number, original invoice, amount, reason, plus any custom fields you define in your own extraction template.
Download the results as Excel (XLSX), CSV or JSON in one click, or pull them programmatically through the LenderAnalyzer API and webhooks into your accounting, ERP or RPA workflow.
Every document is encrypted in transit and at rest and processed under SOC 2 controls, with optional zero-retention purge after extraction. GDPR, HIPAA, SSO/SAML and audit logs are available on enterprise plans.
Start free, or talk to our team about a high-volume enterprise rollout.
