End-to-End AI Solutions

Data Analytics for the enterprise

One reporting layer, and an owner for every definition

In most large organisations the analytics problem is not capability. Every division has tools, analysts and dashboards. The problem is that three of them report a different figure for the same thing, and the executive committee spends its first twenty minutes deciding which number to believe.

Machine Learning for the enterprise — model risk

Model risk, approval, and who signs off before a model reaches a customer

Building a model is now the straightforward part. The question that stalls enterprise programmes is the one asked immediately after the pilot succeeds: on whose authority does this go live, and what happens if it is wrong.

Natural Language Processing for the enterprise

Computer Vision for the enterprise

Rolling vision out across sites, and keeping the sites comparable

A vision system in one plant is a project. The same system across eleven plants is a programme — and the difficulty is not eleven times the first one. It is that the eleven sites have different cameras, different lighting, different line speeds and different definitions of the defect they are supposed to be finding.

Predictive Maintenance for the enterprise

Asset strategy across a fleet or an estate

Predicting a single machine's failure is a well-understood exercise. Doing it across four thousand assets in nine facilities, with maintenance already scheduled by a functioning CMMS and a workforce planned months ahead, is a different discipline.

Personalised Recommendations for the enterprise

Personalisation at scale, and the governance it now requires

Enterprise personalisation is no longer principally an engineering question. It is a consent question, a fairness question and a brand-safety question, and the organisations getting into difficulty are the ones that treated it as a recommendation engine procurement.

Risk Management for the enterprise

Model risk, appetite and regulatory reporting across the group

Boards are being asked what AI is deployed in their organisation, what it decides, and what happens when it is wrong. Most cannot answer, and the gap between the answer and the question is where our risk work sits.

Supply Chain Optimisation for the enterprise

Multi-site planning, and the integration into the ERP you already run

Enterprise supply chain optimisation rarely fails on the mathematics. It fails where the optimiser's recommendation has to become a purchase order in SAP or Oracle, approved by a planner who was not consulted, against a master data set nobody has cleaned since the last migration.

Customer Insights for the enterprise

A single customer view, across business units that do not want to share one

Most enterprises have attempted this at least once. The technology was rarely what defeated it. What defeats it is that four business units each own part of the relationship, each have a definition that suits their reporting, and none have an incentive to adopt somebody else's.