Build a Custom Warehouse Management App with AI

A full warehouse management system is a large investment, and even a good one rarely covers everything. Receiving discrepancies get noted on clipboards. Damaged goods sit in a corner with a sticky note. Cycle count variances are reconciled in a spreadsheet only one supervisor understands.

These are exactly the small, manual workflows that were never big enough for a development project, yet they cost hours every week and make inventory numbers hard to trust.

• Inbound receipts matched against purchase orders, with quantity and damage discrepancies.

• Bin locations by zone, aisle and shelf, with putaway confirmation.

• Stock levels per location for clear warehouse inventory management.

• Cycle counts with assigned zones, counted vs. expected quantity and a variance approval step.

• Pick, pack and ship status per order, with a hold reason for exceptions.

• Quarantine and returns tracking with disposition decisions.

• Roles

  receivers, pickers, shift leads and an inventory controller who approves adjustments.

Stock planning and reorder points belong in a separate inventory management app if purchasing owns them.

A Henosia webinar demo built a fictional operations and inventory app from CSV mock data, with a dashboard, filtering, an inventory and purchasing overview and a simple approval rule. The presenters were clear it was a first version, not a production app. That's the right expectation for yours too.

1. 01

   Create a private project for the warehouse team.

2. 02

   Add mock data

   SKUs, bin locations, open purchase orders and a recent count, as CSV exports.

3. 03

   Connect a database so locations and movements are stored properly.

4. 04

   Plan in Plan mode

   The agent asks about zones, units of measure and approvals, then proposes a plan.

5. 05

   Build and walk the floor

   receive a short shipment, move stock, count a zone.

6. 06

   Iterate, then publish to each shift with the right permissions.

Plan a warehouse app for receiving and cycle counts in one distribution center.
Use skus.csv, bins.csv and open_pos.csv as the data model.
Receivers select a PO, enter quantities received and flag damaged units with a photo.
Shift leads assign cycle counts by zone; variances need inventory controller approval.
Show a daily exceptions list: short receipts, damaged goods, unapproved variances.