Organize chargeback evidence bundles for e-commerce dispute responseautomatically
Automatically organize chargeback evidence documentation by order for streamlined dispute response and case management.
No credit card • Rename in under 3 minutes
sample.pdf
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Date
2024-10-14
Receipt #
102-1234567-123
Issuer
Amazon
Organize chargeback evidence for successful dispute resolution.
- Connect order management systems and evidence collection tools.
- AI extracts order details, communication logs, and supporting documentation.
- Organize by order ID and evidence type for unified dispute case management.
Proof: 1.5k evidence bundles organized last month at 97.3% average confidence.
Before → after filenames
No more download.pdf. Every document follows your naming convention automatically.
receipt.pdf
2024-10-14_Amazon_Order_102-1234567-1234567.pdf
Example naming rule
Rename to 2024-10-14_amazon_102-123456
Why teams adopt this workflow
Complete evidence packages: Compile order confirmations, shipping proofs, communication logs, and policy documents.
Response deadline tracking: Track evidence compilation against dispute response deadlines for timely submission.
Case outcome analysis: Maintain evidence history for analyzing successful dispute strategies and patterns.
How it works
Evidence bundles auto-name to OrderID_Evidence_Bundle.pdf and organize by order with 97%+ accuracy for dispute response.
- Connect order management systems and evidence collection tools.
- AI extracts order details, communication logs, and supporting documentation.
- Organize by order ID and evidence type for unified dispute case management.
FAQ
What types of evidence can it organize?
Organizes order confirmations, shipping proofs, customer communications, and policy documents.
How does it handle multiple evidence types?
Categorizes and organizes different evidence types within each dispute case.
Can it track submission deadlines?
Tracks dispute deadlines and organizes evidence for timely response compilation.
Make it part of your workflow
Connect integrations, use full-text extraction, or call the API for posts processing.
Supported in:
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