Real world AI services and solutions

Delivering the right AI strategies, skills and software solutions

Artificial intelligence is the most important technology of our age, but it is valuable only when it is applied in the real world – enhancing products, improving services and saving lives.

We have partnered with Faculty to help our clients work out what they could do with AI, and then help to do it. This requires three things: the right strategy, the right skills and the right tools.

Whether you are looking to bring insights to decision makers, developing AI enabled solutions or looking for smarter collaboration, the Faculty Platform will provide you with the productivity features, flexibility of open-source tools and scalability of elastic compute resources needed to get the job done.

Delivering on the promise of AI

Artificial Intelligence promises a bright future for both people and organisations – but there are currently very few firms delivering on that promise. In practice, AI is only as good as the available data and how you use that data.

Channel Tools are now working in partnership with Faculty to help clients use the right strategy, the right skills and the right tools to access actionable insights that may be locked within their data. Our team have expertise in all three of these areas and we can help you make artificial intelligence a reality for your organisation.

Our partners have delivered over 350 AI projects in the last four years across sectors ranging from Financial Services and Government, to Retail and Media.

A world-class data science platform

We partner with Faculty, and their platform is one of the industry’s leading data science deployment and workbench toolkits.

The platform makes it easy to write bespoke code that powers your models – and that’s down to our data science team members. All Faculty data scientists are qualified to PhD level and have trained at the world’s leading universities.

The Faculty Platform was created to let clients and scientists concentrate on developing models, not managing infrastructure.