DaaS Explained

Digitisation-as-a-Service (DaaS) delivered by Scan Business serves to act as your comprehensive support partner for all your AI requirements. Yes, we supply the full range of NVIDIA and Intel deep learning optimised components and systems – but we go the extra step in offering access and support for a growing ecosystem of embedded or companion software to enhance and simplify your experience.

In addition to the infrastructure we have a full team of expert consultants including data scientists, Linux engineers and hardware architects to supported your AI development whether it be a proof-of-concept trial, project planning or full deployment.

These specialist teams are available in half-day increments to hand-hold your deep learning projects, or simply to compliment your in-house experts as and when you require. Contact the Scan Business team for further information and rates.

Data Scientist Consultancy

For help and advice with all frameworks, algorithms and interpretation of your deep learning and AI results.

Infrastructure Engineer Consultancy

For help in hardware configuration or software (Linux) set up of your deep learning environment.

Security Consultancy

For help with the security and regulatory compliance aspects of your deep learning project.

Project Consultancy

Ongoing support for longer term projects that may encompass skills sets from all of the above areas.

Introducing Cambridge Consultants

Although our expertise and specialist deep learning team at Scan is always expanding, we recognise when a project is large or complex enough to require a dedicated AI think tank – additional resource in the form of Cambridge Consultants.

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. Cambridge Consultants work 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.

The centrepiece of its ground-breaking development is the Digital Greenhouse. A purpose-built facility designed for discovering, developing and testing machine learning approaches in a fast, secure environment. Inspired by botanical sciences, its 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.

Like Scan’s own proof-of-concept platform, 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 the organically grown deep learning is ready, Cambridge Consultants can export models easily into customers’ own compute facilities or the cloud.

As key strategic partners you can be sure the Scan-Cambridge Consultants relationship will be seamless – always with your project requirements centre stage.

Try DGX solutions in the cloud

We want you to be sure that DGX is right for you, so provide the ability to try your own data on one of our deep learning servers as Proof of Concept. Hosted in a secure datacentre, we will provide you with remote access to a DGX solution so you can evaluate and benchmark it.

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