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

Press release

World’s smartest car park is self-taught and costs next to nothing

20th April 2018

Deep learning is moving out of research and into real-life projects, as we unveil the world’s smartest car park. ‘Goldeneye’ has taught itself to recognise cars and how they appear in spaces


Why AI will continue to flourish

5th April 2018

The current wave of AI was enabled by faster GPUs; the future lies in neural processors and quantum computing. The first industrial revolution of the mid-eighteenth century was sparked by various critical enablers coming...

  • Connectivity & IoT
  • Machine learning & AI
  • Strategic advice

Why can’t a robot harvest a strawberry?

4th April 2018

Picking a strawberry - a simple enough task, but one that’s surprisingly hard to automate. Imagine you’re picking a strawberry. First, you identify your target and move your hand towards it. As you move your arm, you can feel...

  • Machine learning & AI
  • Robotics
  • Sensing

Vlog: smart to intelligent - making AI work for industry

21st March 2018

Artificial Intelligence is about to appear in many more places than face recognition on social media and conversations with Alexa or Siri. The perfect convergence of AI, machine vision and automation means...

  • Data science & analytics
  • Digital services
  • Machine learning & AI



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