ERP & back office · IT & infrastructure · AI integration
Systems rarely fail because of the software. They fail because nobody walked the process with the people running it before deciding what to build.
We come out of manufacturing back offices — accounting, purchasing, operations, and sales. We know what a bad month-end feels like from the inside, not from a requirements document. That's what we bring to the technical work.
We work with mid-market manufacturers and distributors, and with the solution providers who serve them.
Start a conversationWe sit with the people doing the work and find the actual break. Usually it isn't where the org chart says it is.
Not a findings deck and an implementation quote. Working code in your system, scoped small enough to prove itself.
NetSuite and SuiteScript are home ground, but the real work is making systems that weren't designed for each other talk. Any open API is fair game.
Economics
Not because the rate is cheap. Because there are fewer people between the problem and the fix, and every one you remove takes a markup and a round of rework with it.
The rate matters too, and ours sits below the large partner firms — there’s no bench to carry and no layer of management to fund. But the rate is the smaller half of the saving.
Practice one
A few examples from several hundred scripts, integrations, and automations we've put into daily use across manufacturing back offices.
Client detail stays confidential. Happy to walk through the approach behind any of these on a call.
Same pattern every time: walk the process, find where it actually breaks, build the smallest thing that fixes it.
Billing · Revenue timing
Accounts payable · Controls
Treasury · Integration
Practice two
Twenty years running the whole stack for manufacturers — network, servers, identity, phones, and endpoints. The ERP work above only holds up if what sits underneath it is sound, and most of the time nobody is looking after both.
Most of our clients don't want two vendors pointing at each other. One group that understands the ERP and the network behind it removes that argument entirely.
Practice three
Narrow and practical. AI is very good at reading unstructured documents and turning them into structured records, which is most of what a back office does by hand. We build for that, not for chatbots.
We'll also tell you when AI is the wrong tool. Plenty of problems that get pitched as AI projects are a rules change and an afternoon of scripting.
Tips & Use Cases
What the logs showed, the theory that turned out to be wrong, and what actually fixed it.
Costs now reprice monthly whether you do or not. A bigger annual increase fails in both directions — what works is a loop: a margin sensor at order entry, a queue that persists, a console with authority, and a memory that defends each change.
The report that flags thin orders is the easy half. The console that fixes prices held four traps — a swallowed save that hid a whole division, a display function returning account numbers, the discount gross-up, and the override you must refuse to reprice.
“Unexpected token _ in JSON at position 0.” The JSON is fine — a button inside a serverWidget form defaulted to type=submit, and the request you are debugging never left the page.
It shows in the UI and prints empty. A rendered PDF sees stored data, not derived data — and the key you inject has to match what the template is actually looking up.
Get in touch
Tell us what's broken. If we're not the right fit, we'll say so and point you somewhere better.
hello@nesystemsgroup.com