AI is currently the hottest topic in tech. But when we started the CAP AI project (part-funded by the European Regional Development Fund) in 2017, it wasn’t obvious how quickly this sector would evolve. Six years on, we have delivered targeted support to hundreds of companies and founders through CAP AI at the same time as London has developed into a major AI hub. According to some rankings, the UK continues to punch well above its weight in the AI race, with major strengths in talent, research and development. Organisations like ours have not only played a part in building on these strengths but have been instrumental in creating the very ecosystem that allows innovation to thrive. CAP AI has done more than just contribute, we’ve helped catalyse the future of AI in London.

CAP AI was created with the ambitious goal of building London up into a hub of AI research and commercialisation. We designed the project to do this by meeting specific needs of early-stage companies, particularly around AI strategy and talent. 

Tech startups require specialised support, but AI presents an especially complex challenge for small companies. It requires enormous investments of time and money into research, as well as hiring some of the most expensive talent in the world. AI startups thrive on talent, and for any company looking to hire experienced engineers in fields such as natural language processing or deep learning, the financial pressures are enormous – and the need for expert support even more pressing. 

We set out to address these issues through a number of targeted programmes, which together helped to enhance the capacity of startups and strengthen the UK AI ecosystem that thrives today. These programmes included:

  • KEEP (Knowledge Exchange and Embed Partnership) through which we funded 37% of salary costs for startups hiring AI experts;
  • Machine Learning Academy, training the next generation of startup leaders in how to embed ML and AI principles into their businesses;
  • Generative AI Masterclass, training participants in the foundations of large language models (LLMs) and their business applications;
  • The P4 Precision Medicine Accelerator, which has supported scores of companies applying AI and ML tools to personalised medicine;
  • The UCL MSc Business Consulting Project, pairing students from one of London’s premier research universities with SMEs where their analytical skills can be tested against real-world business problems;
  • A partnership with Barts NHS Health Trust, working with Barts Life Sciences to develop AI and ML tools improving early identification of diabetes, heart disease, and other health-related risk factors;
  • An accelerator, Machine Intelligence Garage, delivered by Digital Catapult which supported a number of AI and ML-focused startups. 

Across all the strands of CAP AI, one of the key ways we assisted these companies was helping them access top-tier talent. In some cases, such as KEEP, we provided direct financial support for mission-critical hires; in others, we provided the training which allowed their leaders to better grasp the possibilities of AI and ML for their business. In many cases, that talent played a critical role in the company’s journey.

For instance, one of the earliest KEEP participants was Jump, a careers platform which aimed to speed up the process of job-hunting for office-based employees by better filtering potential opportunities and suggesting the best matches. As Jump’s co-founder, Andrea Consonni, told us when we spoke to him last year, the data engineer they hired with KEEP support played a key role in developing the tech that later led to their acquisition by Jobandtalent, the Spanish unicorn. 

Another testimonial to CAP AI’s impact is the acquisition of Odin Vision, a UCL spinout which we supported in its early stages with fundraising and commercialisation. Odin Vision developed a groundbreaking set of tools for cloud-connected endoscopy and was acquired by Olympus, the Japanese medical device conglomerate, earlier this year. When we interviewed him for our blog, CEO Peter Mountney highlighted the importance of this support securing R&D grant funding and translating research into a product, as well as the value of the Capital Enterprise network for coaching. 

Most remarkably, Odin Vision was acquired within three years of spinning out – a huge success for the Odin team and their investors, but also an unusual one in a sector where angels and VCs often invest with a 7-10 year time horizon. With CAP AI having started in 2016 and running until earlier this year, and the P4 Precision Medicine Accelerator in 2019, many of the companies we have worked with are still years away from maturity.

By the numbers, the single most impactful programmes delivered through CAP AI were Machine Learning Academy and Generative AI Masterclass, which between them supported dozens of startups over their lifetimes. As Job Oyebisi, founder of VR edtech provider StanLab commented, “I highly recommend this programme to any startup entrepreneur who has been thinking about how to apply AI and ML. I learnt so much and my company now has a ML-powered product that we are launching this week.”

The UCL MSc Business Consulting Project helps participants to level up their talent in a different way, by parachuting top-notch student analysts into their companies to bring their skills to bear on specific challenges. Three student analysts were recently deployed to Grantify, a startup that helps SMEs access government grants. With a team of around 50 spread across the UK and US, Grantify is on track to help entrepreneurs secure more than £100 million in non-dilutive funding this year. The student analysts helped Grantify develop internal dashboards tracking client progress, key marketing metrics, and product performance, changes which Grantify CEO Mat Westergreen-Thorn has described as “transformative” for the company.

In the end, the figures speak for themselves: CAP AI supported a total of 300 companies, resulting in the creation of 122 new jobs, the delivery of 88 research projects and the development of 104 new products that attracted £4,872,000 in investment according to ERDF benchmarks. Some companies from CAP AI have gone onto be acquired, one for £66 million; others have raised tens of millions in follow-on funding. We estimate total fundraising by all the companies supported through CAP AI to be over £300 million.

Whilst programme delivery for most strands of the CAP AI project have come to an end, we are looking to the future of AI and how we can continue to support AI startups. Both the P4 Precision Medicine Accelerator and UCL MSc Business Consulting Project will continue to support great medtech companies and SMEs. You can find out about the latest P4 news on their website and we are still recruiting SMEs for future consulting projects – for more information, contact project coordinator Laurel Ye

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