Inventory review from stock and sales CSV exports — Python demo

Self-initiated Rivetfern demonstration using deterministic synthetic stock and 30-day fulfilled-sales exports. No store, customer, supplier, order system or purchasing workflow is connected; this is not paid client work.

The standard-library Python tool validates input schemas, excludes cancelled and out-of-window sales, skips exact duplicate order IDs, quarantines conflicting IDs and flags unknown SKUs. It calculates available units, average daily fulfilled units, lead-time demand, days of cover and a suggested replenishment quantity rounded to the supplied pack multiple. It writes a sorted review CSV, exception CSV, JSON summary and SHA-256 file hashes. Suggestions are prompts for human review; it does not place orders.

I used AI assistance during development, reviewed the code and ran the tests. See the [public case study and code bundle](https://www.twine.net/signin This is transparent arithmetic, not a production forecast. Real use requires current stock and an approved policy for lead time, seasonality, returns and supplier constraints.