What we build.
What it solves.

Before building anything, we map what exists. This means documenting every system, every data flow, every adjustment function, and every manual process across your supply chain. The result is a clear picture of where your grey area lives — the spreadsheets, the manual corrections, the macros that bridge gaps between systems.

This mapping is the foundation for everything else. Without it, any integration project is guessing.

The core of what we do. A Unified Namespace is a central data exchange that sits between all your systems — ERP, MES, planning tools, sensors, spreadsheets — and provides a single, clean, real-time view of your data. Every system publishes to the namespace and subscribes from it. No more point-to-point integrations that multiply every time you add a system.

We build the UNS with a Normalise & Contextualise layer at its boundary. Data is cleaned once, at entry, not by every downstream consumer. This is what converts quadratic integration growth to linear.

The UNS connects everything from high-level business systems down to physical assets on the factory floor.

Full UNS architecture — all inputs normalised through a single namespace, feeding clean data to analytics, AI, simulation, and machine learning.

Your organisation already has the answers — buried in specifications, policies, contracts, regulations, and operating procedures. We build queryable AI systems that sit on top of your own documents, making institutional knowledge accessible to anyone who needs it, when they need it.

This isn't generic ChatGPT. It's domain-specific AI trained on your data, with provenance tracking so you can see exactly which document sourced each answer.

The most undervalued work in data engineering. A demand variable that contains demand plus corrections plus targets plus buffers is useless for forecasting — but this is what most organisations train their models on. We systematically identify which variables have been contaminated by accumulated corrections, separate signal from noise, and rebuild clean data pipelines.

The contaminated variable cycle — how a clean demand signal gets layered with corrections until it's meaningless for forecasting or AI.

Once your data is clean and centralised, simulation becomes possible. We build physics-based simulation models that connect demand and supply, allowing you to test scenarios before committing resources. What happens if a factory goes down? What if demand shifts 20%? What's the optimal production plan given current constraints?

Simulation spanning supply and demand — connecting demand sources and production facilities through centralised scenario modelling.

The final layer: giving leadership real-time visibility into operations with the ability to model interventions before executing them. Current state, scenario simulations, disruption response, and event management — all fed by clean UNS data rather than stale spreadsheets.

Executive intelligence — real-time operations visibility, scenario simulation, and AI-supported decision-making.

Changing an ERP, planning tool, or any major system is one of the highest-risk projects in enterprise IT. With a UNS in place, this risk drops dramatically. Every system connects to the namespace — so swapping one system only requires updating one connection, not every downstream integration.

Without vs. with UNS during a system changeover. The UNS absorbs the transition complexity so downstream systems are unaffected.