When we thought about our approach to enterprise data, the name came quite naturally.

Our corporate background was in a company with one of the most complex data warehouses in the world. Legacy data warehouses were built on top of one another, each with an initial scope to be the ‘source of truth’ but ultimately finding it too complex and expensive to implement.

Instead, build was made on a compromise of requirements and provided piecemeal reporting that fed into an ever-growing web of manual analytical processes for end users to achieve their outcomes.

I was lucky, in that my early days as a customer service consultant inadvertently afforded me access to the source feeds across dozens of key applications. Having no technical literacy at the time, my only frame of reference was the end business purpose of the data I was looking at.

Seeking technical mentorship, I slowly started translating my business knowledge into data modelling and development. There was clear transformational potential in having complete, holistic datasets that represented what was really going on in the systems day to day.

Data Revolutions

So much of our work – be it customer service consultants, account managers, operational analysts or product managers – is built around the gathering and time-consuming interpretation of vast sums of data. If you could raise the standard of awareness and understanding of fundamental truths within the systems, it would be a revolution!

Work would be simplified, customers better serviced and general intelligence would be raised across the company.

How to approach such an ambition? There were around 13 different applications to work across, each application holding an average of 40 tables, with hundreds of billions of transaction records stored across the board. It seemed natural to implement a modular approach; as an area of system behaviour was logically defined it would be programmatically implemented as a module.

Over the many iterations around 140 modules were implemented, representing every area of system behaviour across the network of applications. Individually, these modules served little except the satisfaction of their creators. Together, they formed the production of an enterprise-wide transformation layer that was adopted across the company and drove upwards of £40 million of trackable revenue benefits.

A proof-of-concept for a real Thinking Machine.

Team Machine

Today, we are taking inspiration from these experiences to bring innovative data solutions to the global market. We have built a core team of seasoned experts and thought leaders, almost all of whom were mentors and guides in years past.

Together, our mission is to be positioned as a strong player in the next wave of workplace automation, powered by intelligent modelling and integration of network-based data.

Stay tuned for our starting products in the Telecom & Renewable Energy space…

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