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From manual to automatic in four steps
No migration. No rip-and-replace. No eighteen-month implementation. We build on top of the ERP your team already knows, and we start with one process rather than all of them.
The process, step by step
Each stage has a clear output, so you always know what happens next and what it depends on.
1. Discovery
We sit with the people doing the work and map how orders and information actually move through your business — including the workarounds nobody documented. Then we rank the tasks by hours burned and pick the first one together.
- Typically one to two sessions
- Includes your real order formats and edge cases
- You get the process map whether you proceed or not
2. Build
We configure the automation and test it against your real historic data in a sandbox — not a demo dataset. You see the output before anything touches your live ERP, and we tune it until the results are right every time.
- Tested on your own past orders
- Nothing writes to live data until you approve
- Edge cases handled before go-live, not after
3. Go live
We switch on in stages. For the first period the automation runs alongside your existing process so your team can compare, build trust, and stop double-handling when they’re ready — not when we say so.
- Staged rollout, not a big-bang cutover
- Your team trained on the exception queue
- Roll back at any point
4. Optimise
Automations aren’t set-and-forget. We monitor performance, tune the edge cases that surface in the real world, and once the first process is clearly paying for itself, we look at the next one.
- Ongoing monitoring included in every plan
- Regular optimisation reviews
- Add processes as you grow
Why AI matters here, specifically
Traditional integrations need everything in a predictable format. Real businesses don’t work that way.
A rules-only integration breaks the moment a buyer renames a column, sends a PDF instead of a spreadsheet, or writes “same as last time, plus 12 of the navy” in an email. That’s why so many ERP integrations quietly get abandoned.
The AI layer reads intent, not just structure. It handles the messy formats a person would understand at a glance — and, critically, it knows when it isn’t sure and hands the job to a human instead of guessing.
Automation you can actually trust
Handing over a process only works if you can see what it did and stop it when you need to.
Exceptions never guess
If the automation isn’t confident — an unknown SKU, a price that doesn’t match, a quantity that looks wrong — it stops and asks a person. Silent errors are the one thing worse than manual entry.
Every action is logged
You can see exactly what was processed, when, and what the automation decided. If something needs checking, the trail is there — no black box.
Credentials stay yours
We connect through your ERP’s supported integration methods, with access you grant and can revoke at any time. We only touch the data the automation needs.
Implementation questions
Discovery needs a few hours from the people who run the process day to day — they know the edge cases nobody wrote down. After that the build is on us. Your team’s next real involvement is reviewing the test output and signing off before go-live.
Expected. Adjusting an existing automation is part of your plan, not a change request with a quote attached. Bigger changes get scoped like any new automation.
We connect using your ERP’s supported integration methods with credentials you create and control. You can scope the access, see what it’s used for, and revoke it at any time.
Failures alert us and you — they don’t sit silently in a queue. Because we roll out in stages alongside your existing process, there is always a manual fallback while confidence is being built.
We’d prefer it. Starting narrow means you see a result quickly and the automation is proven on real data before you commit more of your operation to it.
Bring us your messiest process.
Thirty minutes, your real orders, and an honest answer on whether automation is worth it.