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Audit Trails for AI Document Workflows: What To Store

DEV Community·Iteration Layer·19 days ago
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Logs Are Not An Audit Trail The first audit trail in many document workflows is accidental. A developer logs the extraction response. The queue records a job ID. The webhook target stores the payload. The error tracker captures a failed request. For a while, that feels good enough. Then someone asks a real operational question. Why did this generated PDF contain the wrong supplier address? Which version of the extraction schema ran? Was the invoice total accepted automatically or corrected by a reviewer? Did the failed email mean the extraction failed, or only delivery? Which customer document produced the row that finance imported? Application logs help developers debug. They are not designed to answer those questions reliably. Logs are often sampled, redacted, deleted, duplicated, or spread across tools. They describe what the application happened to emit, not the durable history the product needs. An audit trail for AI document workflows should be built from records, not scattered log lines.…

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