Cold-storage and refrigerated-transport operators run a business where the product is only as good as its temperature history, and ERPNext core has no concept of temperature at all. A Warehouse is a name and a tree node; it does not know it holds -18 °C frozen goods versus a +2 °C chiller, and nothing stops a picker moving a pallet from one to the other. Batch carries an expiry date but ERPNext's picking logic offers FIFO by creation, not FEFO by expiry, so short-dated stock quietly ages out at the back of a rack. Excursions — a door left open, a reefer unit that tripped overnight, a failed pre-cool before loading — get written in a WhatsApp message or a paper log with no link at all to the Stock Entry, Batch or Delivery Note they affect. When an auditor or a customer asks "prove this pallet never went above 4 °C", the answer is assembled by hand from three systems.

We build a proper Frappe app — its own repo, its own module, installed on your bench alongside erpnext — rather than a pile of Custom Fields on a production site. The core of it is a Temperature Zone DocType linked to Warehouse, defining a min/max setpoint band, tolerance, and the product classes allowed to rest there. A before_submit doc event registered in hooks.py on Stock Entry, Stock Reconciliation, Purchase Receipt and Delivery Note validates every target warehouse against the item's required zone, so an incompatible movement is refused at submit rather than discovered at audit. FEFO is implemented as a whitelisted method that overrides batch selection: for each row it queries Batch ordered by expiry_date ascending, filtered to batches actually in the picking warehouse with positive Stock Ledger Entry balance, honours a configurable minimum-remaining-shelf-life rule per customer or item group, and writes the allocation back into the Pick List — with a client script that shows the picker why a specific batch was chosen and blocks a manual override without a reason code.

Excursions become first-class records. A Temperature Excursion DocType captures the asset (warehouse, chamber, or reefer), the start and end timestamp, peak and trough readings, duration above tolerance, root cause, and the corrective action taken. Readings can arrive by whitelisted REST endpoint from your existing loggers or telematics platform, by CSV import, or by manual entry on a mobile form; a scheduler event defined in hooks.py runs on a short interval to sweep unresolved excursions, escalate by role via Notification, and flag the affected batches. Because the excursion links directly to Batch and Serial No, an affected lot can be put on a hold status that both the FEFO allocator and the Delivery Note validation respect — quarantined stock cannot be picked or shipped until quality releases it.

On the transport side, a Reefer Trip DocType plans a run against a vehicle, a driver, a temperature setpoint and a list of Delivery Note stops, with capacity and compatibility checks so a frozen and a chilled consignment are not loaded into a single-zone box without an explicit multi-temp vehicle profile. Pre-cool confirmation, door-open events and per-stop delivery temperature are captured against the trip. Compliance documentation is generated from that data: batch genealogy and temperature-history reports as Query Reports and print formats, exportable per shipment for HACCP, GDP or customer-specific audit packs. Everything ships behind proper Role Profiles and permission rules — a warehouse operator can log a reading, only quality can release a held batch, only a supervisor can override FEFO — and every override is written to the document's own audit trail. All records are reachable over the Frappe REST API, so your WMS, telematics or customer portal can read and write against the same objects.

This is a build-to-order product, not a marketplace download. You request a quotation, we run a short scoping call, and we write the specification against your actual zones, product classes, vehicle types and audit obligations — the shape of a pharmaceutical GDP operation is not the shape of an ice-cream distributor. From confirmed scope, typical delivery is two to four weeks: we build against Frappe/ERPNext v15 or v16 to match your bench, deploy to a staging site for UAT with your data, then install on production in an agreed window with a tested rollback. You receive the full source, the git repository, technical and user documentation, a training session, and a post-go-live support window.