Stock watched around the clock,
reorders drafted before you run out

The process today

Most teams track stock the same way: a spreadsheet or a dashboard that somebody opens on a schedule, usually once a week, sometimes once a month if things are busy. Between those checks, a fast-moving SKU can quietly run out, and a slow one can keep getting reordered out of habit because nobody noticed the shelf was already full. By the time a stockout shows up in a sales report, the order has already been missed, the lead time has already started working against you, and a customer has already seen “out of stock” or a longer delivery estimate than usual.

The underlying problem is not that anyone is careless. It is that watching every SKU every day against its own reorder point, its own supplier lead time, and its own recent sales velocity is not a task a person can do consistently across a catalogue of any real size. A buyer with two hundred SKUs and a dozen suppliers is making the same judgment call over and over, often from memory or gut feel about which items “usually” need attention, which means the SKUs that do not usually need attention are exactly the ones that get missed when they suddenly do.

Overstock is the quieter cost of the same gap. A slow mover that keeps getting reordered because last quarter’s numbers looked fine ties up cash and warehouse space that a faster-moving item could use instead. Nobody decided to overstock it; nobody had the bandwidth to notice the trend had changed before the next purchase order went out.

What the agent does

The agent checks stock levels against the reorder point you set for each SKU, on a schedule rather than whenever someone remembers to look, and factors in the supplier’s actual lead time so a reorder is timed to arrive before the shelf empties, not after. When a SKU crosses its threshold, the agent drafts a purchase request with a suggested quantity and sends it for approval rather than placing the order itself.

Alongside reorder monitoring, the agent flags slow movers and overstock using the same sales data, so a buyer sees both ends of the problem in one place: items about to run out and items that have been sitting too long. Alerts route to the right person by category or supplier, so a buyer who only handles packaging is not getting pinged about electronics components, and a weekly stock-health summary gives a manager the shape of the whole catalogue without reading every individual alert. The agent typically connects to Shopify, a marketplace back office, an ERP system, or a plain spreadsheet, whichever one actually holds your stock numbers today, rather than asking you to migrate data into a new system first.

Every check, every alert, and every draft purchase request is written to a log, so a buyer reviewing a reorder a week later can see exactly what stock level and sales trend triggered it.

What stays with humans

A buyer still decides the actual order quantity, the supplier to use when more than one option exists, and whether a seasonal spike or a one-off promotion should change the normal reorder math, since the agent works from recent sales history and does not know a marketing campaign is about to launch next week. Negotiating terms with a supplier, deciding to drop a SKU entirely, and approving any purchase request before it becomes a real order against a real budget all stay with a person.

Guards

Every purchase request the agent drafts needs human approval before it is sent to a supplier, so the agent flags spending decisions, it never makes one on its own. The full history, every alert raised and every draft purchase request created, is logged so a manager can trace back why a particular order was suggested and when. Reorder rules and lead times are set by your team and can be adjusted at any time, and a weekly summary gives a sanity check on the whole system rather than relying on individual alerts never being missed.

Price and timeline

Running cost is usually $15 to $60 a month in model usage depending on catalogue size, with a budget cap set before launch.

Related

This pairs naturally with purchase order processing, which picks up once a draft request is approved, with shipment tracking updates so you know when the reordered stock is actually on its way, and with vendor comparison for procurement when more than one supplier can fill the same order. For a sense of what this looks like at scale, the digital goods marketplace automation case study covers a catalogue of over 25,000 listings with its own pricing and delivery guards, and ProBay describes a marketplace we run ourselves with a margin guard checked against hundreds of real orders. See the broader picture on the AI agents service page and the automation-everything overview.

Want to know what your reorder points and lead times would look like running on autopilot? Get in touch and we will walk through your current stock list on the first call.

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