Machine learning is at the core of a new wave of artificial intelligence applications limited only by our imagination.

New algorithmic approaches, recent jumps in processing power and large training data sets generated by internet users mean that, for the first time, machines can learn to solve useful problems without explicit programming.

Infinite possibilities

We’re working at the frontier of this vital, transformative technology, developing systems that leverage deep learning techniques to achieve unprecedented performance in a huge range of applications.

From detecting anomalies and attacks in networks and learning to control legacy systems to high-performance audio and image processing and interpretation, optimising infrastructure deployment and natural communication with humans, the possibilities are endless.

Welcome to the Digital Greenhouse

The Digital Greenhouse is a purpose-built facility designed for discovering, developing and testing machine learning approaches in a fast, secure environment.

Inspired by botanical sciences, our team ‘grows’ hundreds of strains of models to understand where the richest pickings are to be found – beyond the confines of ordinary software development methodologies. New algorithmic hopefuls are assessed against long-standing commercial and industrial challenges, such as optimising the deployment of cellular infrastructure or detecting anomalies on a manufacturing line.

State-of-the-art compute resource

The Digital Greenhouse runs on high-performance computing based around NVIDIA’s DGX-1 Deep Learning Supercomputer and other GPU- and FPGA-accelerated servers, providing petaflop-scale compute on-site.

This links to petabyte-scale local storage, project-specific clouds and our continuous integration systems. When our organically grown machine learning is ready, we can export models easily to customers’ own compute facilities or the cloud.


Versatility and breadth

Our machine learning expertise spans older, established techniques such as Bayesian inference and support vector machines, through to the latest advances in deep learning, generative networks, natural language processing and unsupervised learning.

We can design, develop and deploy sophisticated bespoke machine learning systems from the ground up or work with third-party services and platforms. Particular specialities include real-time/low-latency processing at the network edge, lower power silicon design for machine learning and tools that allow deep learning to be trained effectively with much smaller datasets than is typically believed possible.

Tech, tools & facilities

Digital Greenhouse

Digital Greenhouse

The Digital Greenhouse is our purpose-built AI research facility, specifically designed to discover, develop and test machine learning approaches in a fast, secure environment. The facility features an NVIDIA DGX-1 Deep Learning Supercomputer, a bank of machine learning computers, petabyte local storage and many teraflops of dedicated compute power.

Case studies

Case study

The Aficionado

We set ourselves the challenge of creating a machine learning system that could address the infinitely complex world of music. The result is The Aficionado.


Analog devices smart car park monitoring

Paving the way for low-cost, real-time sensing for smart buildings and smart cities, using machine vision and a low-cost processing platform


Pick of the bunch

Nature doesn’t provide blueprints, which are why our robot system can cope with handling all kinds of different fruit – and can even sort red apples from green ones.

News & insights


Experiential sensing

1st June 2018

As major brands strive to maintain consumer relevance, innovative brands will turn to technology for a deeper understanding of their customers.

  • Digital services
  • Machine learning & AI
  • Sensing

Sensing the need for cockpit innovation

30th May 2018

There’s a lot written about new sensors that are used in cars to make them more autonomous or safer. LIDAR, radar and externally facing cameras are often mentioned. However, in the automotive market...

  • Cloud/scalable systems
  • Connectivity & IoT
  • Electronics & ASICs
  • Machine learning & AI

Force feedback machining

23rd May 2018

Today’s machine tools are already incredibly sophisticated pieces of technology, but advances in sensing capability and machine learning will enable a step change in manufacturing processes.

  • Machine learning & AI
  • Mechanical engineering

Diary of a developer (part 2) – user stories

22nd May 2018

As technology consultants, we know all too well that it takes a lot to turn an innovative idea into an engaging product – or, in this case, demo! – that meets the varied needs of its users. My colleague Jo Davies recently blogged...

  • Human factors
  • Machine learning & AI



AgTech Nexus USA 2018

Harvard Club, Boston, MA

A two-day conference where agribusinesses, investors, tech companies and other stakeholders will be immersed in the innovations and investment opportunities surrounding this exciting sector.


IoD Cambridgeshire

19th Jun 2018
Barclays Eagle Labs Incubator, Cambridge

Paul Beastall, Director of Technology Strategy at Cambridge Consultants, will join leaders from across the industry to speak at the IoD Cambridgeshire: AI; Think you know your ABCD? event.


AI in Pharma Summit 2018

9th Oct 2018
The State Room, Boston, MA

Join us as we exhibit for the first time at the AI in Pharma Summit 2018. Jaquie Finn, Head of Digital Health, will be speaking at the summit. Jaquie provides strategic guidance and practical support for clients transitioning...

We can help you achieve the impossible