Retail inventory system demo: 8 live apps built by AI models
Every app below is a working retail inventory system, built by an AI coding model from the PlanSmith Retail Inventory Management planner. They all run with sample data. Open one, sign in with the demo account it shows, and try it.
Open one and try it.
LiveStockbay
“Stockbay” is a movement-ledger purist: stock only ever changes through receiving, adjustments, counts, or returns, each writing before/after quantities with actor attribution. Fifteen areas (matrix items, scan, stocktakes, SVG label sheets, CSV opening-stock import, vendor returns, an audit trail) and eight CSV exports behind three role-aware logins.
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LiveHarbor Lane Market
A single-store stock command center finished after the original audit. It has the full ops loop: purchase-order pipeline (draft → sent → partial), receiving against POs, counts with variance, vendor returns, labels, and reason-coded adjustments, all behind real credentialed logins and a dashboard whose every widget names its data source.
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LiveNorthstar Goods
“Retail Inventory Command” has every screen implemented with zero stubs: a drill-through KPI dashboard, items and variants, adjustments, stocktakes, low-stock rules, POs and receiving, vendor returns, labels and scan, and CSV exports, with four-role access control.
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LiveStockKind
“StockKind Inventory Command” is a zero-dependency build with the set's most data-visual dashboard: a stock-health score, category value mix, a risk-ranked reorder queue that composes POs, receiving with partial receipts, counts with variance commit, and seven CSV reports.
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LiveNorthline Outfitters
The broadest operations lifecycle of the set: receiving, vendor returns, adjustments with reason codes, full and cycle stocktakes, labels, scan workflows, CSV import, owner valuation, and eight exportable reports, over a real 22-table SQL schema with zero dependencies.
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LiveCommand Center
“Northstar Retail Supply” is a scan-first clerk workbench and owner command center: counts with live variance, receiving against POs and ad-hoc, unresolved-barcode reconciliation, labels, and role-gated valuation, over a rich cross-linked demo dataset.
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Same planner, different results.
| Rank | Build | Model | Score | In one line |
|---|---|---|---|---|
| 1 | Harbor Lane | Composer 2.5 | 93 | The strongest build on both features and design. |
| 2 | Stockbay | Grok 4.5 | 91 | The second Grok lane, and the set's cleanest domain model. |
| 3 | Northstar Goods | GPT-5.5 | 87 | The consistent all-rounder: every screen, no stubs. |
| 4 | StockKind | GPT-5.5 | 86 | The most presentable handover, and it runs on nothing. |
| 5 | Command Center | GPT-5.5 | 81 | Strong everywhere, exceptional nowhere. |
| 6 | Northline Outfitters | GPT-5.5 | 77 | The broadest lifecycle in the set, behind the plainest UI. |
| 7 | Larder | Gemini 3.1 Pro | 62 | Highest ceiling on paper; took three fix rounds to get there. |
| 8 | Harbor Lane Market | Grok 4.5 | 35 | Missed the audit window; the finished build is real. |
Scores are as found at audit. The full findings for every build, both what it does well and what went wrong, are on the retail inventory management build-off board.
What to know before you build.
- Spare parts reorder points: min/max levels with Excel examples
- Parts stocktake: a worked example, count sheet and checklist
- Construction inventory management software: what it must do
- Auto parts inventory management: what the system must do
- Inventory database design: schema, SQL template, ER diagram
- Custom inventory management software: what you're paying for, and when it's the wrong answer
- Inventory management in Excel: a working template, where it breaks, and what comes next
- Free inventory management software: what 'free' costs, and how to choose
- What a retail inventory management system includes (feature checklist from 120 real sources)
- How to build a retail inventory management system: the practitioner's guide (2026)
- Build vs buy: retail inventory management in 2026