When rows need to be normalized and split by market, the transformation should be reproducible: defined mapping, explicit validation, visible exceptions and output verification.
ShadowOrders product: CSV/XLSX Data Cleanup & QA. This page describes one specific use case; the technical boundary is the same as the underlying product.
The current deterministic fixture demonstrates accepted rows, rejected rows and separate market outputs with roundtrip verification. The service is intentionally bounded so unsupported transformations are identified before paid work begins.
Send the actual column shape and the desired output split. ShadowOrders confirms whether the job fits the managed cleanup pipeline before accepting payment.
No invented source values and no hidden “fixes” to rejected rows. Ambiguity is surfaced for review.
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