You don’t commit to a big build up front. The audit comes first, then you decide what to implement — one piece at a time.
We map your whole operation — manufacturing, the channels, the seller network, finance — and find where AI saves money and where it doesn’t belong.
Every opportunity ranked by impact vs. effort. You see exactly what’s cheap to build, high-impact, and worth doing first — with the cost of each.
We build the highest-value, lowest-cost item first as proof. It works, you see the return, then you choose what’s next. No single large bill.
If the audit doesn’t find enough recoverable waste to justify its cost, you pay nothing and keep everything we produce. 15+ audits delivered, no refunds to date.
Anonymised under NDA (named case studies are being recorded now). We’ve not audited a perfume house yet — but we’ve audited the three things Milton-Lloyd is.
A products company selling into a large network of accounts through field reps. The reps were spending around 32 hours a week each visiting low-value accounts (worth $5–7K/yr) instead of winning new ones — $83,200/yr of misdirected effort, the single biggest leak. There was no visibility on who was doing what, leads went cold after one missed call, and the account base had been flat for two years — gaining roughly 40 accounts a year but quietly losing as many.
Your seller network is the same shape: a large base of accounts that need onboarding, attention and retention. Without a system, effort drifts to whoever shouts loudest, new sellers go cold, and you can’t see which accounts are growing versus quietly churning. AI fixes exactly this — auto-qualifying and prioritising sellers, flagging the ones going quiet, and freeing your team to grow the network instead of just maintaining it.
A business onboarding 300–400 new customers a year on a fully manual stack — dragging people through pipelines by hand and re-entering the same data across five tools, with 15 hours a week lost just to spreadsheet management. Revenue was leaking because only a fraction of customers were ever properly invoiced and followed up. A single automation — automated invoice and instalment tracking — recovered $47,923/yr on its own, built in half a week.
“Free accounts, set up in minutes” means a flood of sign-ups and orders with no system catching what slips through — sample buyers never followed up to a full-size sale, referral codes that aren’t tracked, repeat orders that don’t get nudged. The lesson: one well-chosen AI automation can pay back the entire audit before anything else is touched.
A manufacturer paying for capable, expensive software that simply didn’t talk to itself. Orders and projects were re-created by hand across three separate systems, ledger reconciliation ran in spreadsheets, and invoices got double-paid because nothing cross-checked. In their words: “We’re not moving any data yet — that’s our problem.”
You sell direct, on Amazon, and through resellers — three channels pulling from the same stock. When they don’t connect, someone re-keys orders, stock counts drift, and money leaks through the cracks: over-selling, double handling, missed reconciliation. AI automations move that data for you and cross-check it, so the channels stay in sync without the manual glue.
This is the part that matters most: you stay in control of spend at every step.
Implementation is always scoped case by case — but here’s the realistic range, so there are no surprises. You only ever pay for the pieces you approve.
| Phase | What it is | Typical cost |
|---|---|---|
| The audit | Full operational audit, live portal, and priority matrix. Money-back guaranteed. | ~$10,000 |
| AI co-worker plugins ← start here |
AI assistants built into the tools your team already uses — drafting customer replies, answering order and stock queries, and clearing repetitive admin. Fastest return, lowest cost. | $2,000–$4,000 per build |
| AI process automations | AI that moves your data for you — orders and stock kept in sync across your own store, Amazon and the seller network, with no manual re-keying or double entry. | $4,000–$15,000 per build |
| AI agents & decisioning | AI that does the thinking — qualifying and onboarding new sellers, forecasting demand from your sales data, and flagging churn or stock risks before they cost you. | $15,000–$40,000 per build |
| Larger bespoke AI builds | Bigger, tailored AI systems for a specific part of the operation, scoped directly from the audit findings. | up to ~$70,000 by scope |
Most businesses start with a single AI co-worker plugin and grow from there. You are never quoted one large implementation figure — the priority matrix tells you exactly which builds are worth it, and you approve each one individually.
A small monthly retainer keeps us on hand — questions answered, quick calls when you need them, and continuous optimisation of what’s already live. On top of that, you pay a per-build fee only for the pieces you approve.
This is deliberately different from a retainer that sits unused. It’s tied to active delivery and scoped to what you actually choose to build — so you’re never paying for something that isn’t moving the business forward.
A complete sample — process map, findings, priority matrix and full plan. Different industry, simulated data, but exactly the deliverable you’d receive.
Start with the audit. It’s guaranteed, it gives you the full picture and the priority matrix, and it’s the only thing you commit to up front. Everything after that is your call, one step at a time.