Inventory management systems that keep one honest stock figure

We build scanning workflows for receipting, put away, picking, packing and transfers, running on rugged handhelds or on ordinary phones depending on the environment and the budget. Crucially, these screens work offline. Warehouse wifi is unreliable in exactly the places you need it most, such as the far aisle, the cold room and the yard. Transactions queue on the device with a visible sync indicator and upload when coverage returns, with conflict rules agreed in advance for the case where two people touch the same bin. We also replace the annual shutdown stocktake with rolling cycle counts, where a small number of locations are counted each week and prioritised by value and movement. That finds errors while they are still explainable, and most operations stop needing a full shutdown count within a year.

A system that models only on hand will lie to you constantly in those situations. We model each state explicitly, so available to promise reflects what a salesperson can actually commit today, and the balance sheet reflects what you actually own. Transfers between sites are two sided transactions with a receipting step, so freight discrepancies are caught at the destination rather than absorbed into a general variance. For distributors running several states this is usually the single change that ends the argument between branches about whose count is wrong.

We build forecasting as decision support rather than automation. The system proposes reorder quantities based on demand history, lead time by supplier, seasonality and a service level you set per item class, then shows its reasoning: this is the recent run rate, this is the supplier's actual lead time over the past year rather than the one on the contract, this is the safety stock implied. The buyer approves, adjusts or rejects, and their overrides are recorded so the model can be assessed against them later. Slow moving and obsolete stock reporting matters just as much, because capital tied up in dead lines is invisible until someone reports on it.

There is also a strong off-the-shelf market for mid sized operations, and we will point you at it when it fits. Custom becomes the better answer when your stock behaves in ways packaged products handle badly: kitting and assembly, batch or serial traceability with recall obligations, consignment, unusual units of measure, or pricing and allocation rules tied to contracts. Manufacturers frequently land there, which is why this work often sits alongside our manufacturing systems, and retailers with both stores and online usually need it once stock accuracy starts affecting retail fulfilment promises. If your real problem is that your store and your warehouse do not talk, that may just be an integration job, closer to API development than to a new system.