Services
ERP Solutions
Unified finance, inventory, sales and procurement systems with AI forecasting and anomaly detection built in.
Most ERP rollouts fail the same way: a single generic configuration gets forced onto a business's actual processes instead of the other way around, and the result is a system employees route around with spreadsheets within a year.
It's a solvable problem, not an inherent one. Organisations with genuinely connected, well-integrated data report dramatically higher returns on the systems built on top of it than those without, and most of what looks like "the ERP doesn't work" actually traces back to disconnected modules and manual reconciliation bolted on afterward — not the core system itself.
We map how the business actually operates before writing any code, then build a unified system — finance, inventory, sales, procurement and HR — with AI layered in specifically where it changes outcomes: per-SKU demand forecasting instead of one static rule for the whole catalogue, automated anomaly detection on transactions instead of a manual month-end reconciliation, and executive dashboards that answer a plain-language question instead of requiring a report request. Rollout is modular, with core modules live early, and role-based access and a full audit trail run through every module from day one.
AI forecasting specifically outperforms a single static reorder rule because it works from actual granular signals — sales velocity, seasonality, promotional calendars and supplier lead time, per SKU — rather than one buffer applied to an entire catalogue. Ensemble forecasting methods at this level of granularity now materially outperform traditional statistical forecasting, which is exactly why fast-movers stop stocking out while slow-movers stop tying up capital, at the same time, on the same system.
Frequently asked
We already have an ERP. Can you improve it instead of replacing it?
Often, yes. A lot of ERP pain isn't the core system — it's disconnected modules, no forecasting layer, and manual reconciliation bolted on top. We start with an assessment of what's actually broken before recommending a rebuild versus a targeted AI or integration layer on what you have.
How does AI forecasting actually improve on a standard reorder rule?
A standard rule uses one fixed buffer for the whole catalogue. A probabilistic forecast produces a full range of likely demand per SKU, so safety stock is calculated per item from its actual sales velocity, seasonality and supplier lead time — preventing the fast-movers-stock-out-while-slow-movers-overstock problem a single rule causes.
How long does an ERP rollout take?
It depends heavily on module count and legacy data quality, but a modular rollout means core modules — usually finance and inventory — go live well before the full system is complete, so the business sees value in months, not only at the very end of a multi-year project.
Does AI forecasting require ripping out our existing finance and inventory systems?
No, but it does need clean access to them. Accurate forecasting needs synchronized master data and financial reconciliation, plus live inventory movement, lead-time and pricing data flowing in from wherever it currently lives — often an existing ERP, WMS or OMS. We integrate against what you have first, and only recommend replacing a system when the integration itself turns out to be the actual bottleneck.