Convexity vs spreadsheets, inventory tools and ERP suites

Written by the Convexity team. Short answer: keep what works. If your ERP handles transactions well and the trouble is deciding what to buy, add forecasting and purchasing next to it. If you are running on spreadsheets and QuickBooks with thousands of SKUs, you probably need a real inventory system, and that is where Convexity usually fits.

Where hard-goods teams actually get stuck

The data usually exists. It is split across the ERP, the online store, warehouse reports, supplier files and a few spreadsheets. The pain shows up at handoffs: a rep needs to know if 100 units are free, a buyer needs stock and demand in one place to place a PO, the warehouse needs an exception sorted before it can ship.

Convexity connects those handoffs around the systems you keep. We start with one task, list the records, rules, approvals and exceptions it involves, and tell you what is standard, what needs configuration and what stays out of scope.

You work with the people who build it

Our founders and engineers run your onboarding and stay reachable after go-live. One of them ran purchasing and inventory at Wayfair; another built supply chain products at Microsoft. When something in your process is odd, you explain it once, to someone who can change the product.

We fit the software to your process

We start from how your team actually takes orders and buys stock, including the exceptions. Before we build anything, we tell you which parts are standard, which need configuration and which would be custom work, and we put that in the proposal.

AI that can act, inside limits you set

Convexity connects Claude, ChatGPT or Gemini to your records through MCP. Depending on the permissions you grant, an assistant can look into a stock problem, draft a purchase order or create a sales order from an emailed PO. Anything that spends money or leaves the building still goes to a person to approve.

Grow without hiring people to retype orders

The point is for the team you have to handle more orders, SKUs and suppliers without adding headcount just to rekey data or merge reports. How much that frees up depends on your data and process, so we measure it on your own workflow instead of quoting a number up front.

Fix one workflow, then expand

You do not need to replace every system to make progress. Pick one job, such as entering customer orders, investigating stock or preparing the weekly buy, and get it working with the people who do it. Measure the result, then move on to the next.

Where AI helps and where it should not decide alone

AI is useful for digging through records, preparing an order or flagging an exception in the middle of real work. It should always show where its numbers came from. Before it changes stock, sends a message or creates a purchase order, decide who approves that and what happens if it fails.

Which option fits which problem

When something else is the better choice

Keep your ERP if it already does the job and you can maintain it. Pick a specialist tool if the real need is narrow, like production scheduling, retailer EDI, marketplace repricing or regulated lot traceability. Pick an enterprise suite if you need its full breadth. Look at Convexity when the problem is inventory and purchasing across many SKUs and channels.

Give every option the same test

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  One item with a stock unit, case pack, supplier minimum and lead time.

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  One customer order that needs a reservation or allocation decision.

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  One purchase order with a moved date or a short delivery, and the buying decision it changes.

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  One problem record: a missing item, a wrong price, stale stock, a duplicate update or a dropped connection.

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  For every handoff: the system of record, refresh timing, allowed writes, approver and recovery.

Ask each vendor to walk the same case and say what is standard, configured, custom or unsupported. A feature list does not show that your record, approval and exception will actually make it through.