A taste of the London AI Ecosystem

“London has technology, finance, and government — it’s like SF/NYC/DC in one city. And within an hour by train, you have access to four world-leading research universities in addition to the Alan Turing Institute.” — Thomas Stone, partner at AI Seed

When new to London, it can be challenging to get a sense of the metropolitan AI ecosystem. In this article, we’re going to give you a snapshot of the AI activity in London presenting insights from our ambassadors, insiders, and experts.

We’re going to break this snapshot of the London AI Ecosystem into three sections — Section A will focus on Business; Section B will focus on Supporting Institutions; and Section C will focus on Community. Under each of these sections, we will highlight companies, institutions, or organisations you should be watching because they’ll help you better understand AI activity in London and/or due to their unique or prominent contribution to the ecosystem.

Our passion for London AI business is supported by ING.

Doron Reuter, responsible for new AI products and partnerships at ING Wholesale Banking said: “London provides a tremendous opportunity for data scientists, engineers, designers and product managers to work on AI products using cutting-edge machine learning methodologies; especially in the finance sector. This is why ING Wholesale Banking Advanced Analytics is establishing a team in London that will work within the London financial ecosystem to apply AI for a reliable, healthy and sustainable finance sector.”

Section A: Business

The London AI ecosystem consists of an amalgamation of industries, with AI having its fingers in just about every pie the City has to offer. The story of AI in London is one of rapid growth and relative youth; the rate at which AI companies were being founded doubled between 2011–13 and 2014–16 and this expansion was so rapid that by the end of 2016 over 60% of all UK AI companies were founded in the prior 36 months. It’s therefore unsurprising that the ecosystem is still young, with three quarters of UK AI companies being in the early stages of growth either at ‘seed’ ($0.5m-$2m) or ‘angel’ (<$0.5m) level funding.

“London has a vibrant tech ecosystem, built up over the past two decades. This tech ecosystem includes active angel investors, great incubator and accelerator programmes, and a full slew of later stage capital. But perhaps more importantly, it includes hundreds of founders and many companies who are actively using machine learning or other AI techniques in their businesses.” — Azeem Azhar

Between 2008–2017 global startup creation grew by 24% on average each year, however, London saw nearly double that growth in the same period, as startup creation grew by an average of 42% a year. It may therefore not be surprising that London’s AI ecosystem is both diverse and fertile — with unique applications of AI in multiple industries being well-supported with talent from the outstanding educational programmes, and with investment opportunities and clientele from the well-developed industries in the city. Clearly, the ecosystem is developing fast, AI companies were being founded on a near weekly basis leading into 2017. So to keep up with this fast growing environment and to point you in the right direction no matter what your involvement with the ecosystem, we’re going to introduce you to three exciting companies in three sectors ripe for AI innovation.

“A critical mass of scientific and engineering talent contributed to London becoming an early pioneer. Innovation is emerging not only from within single technical disciplines or domain areas but in the spaces between them — from synthetic bio technology, computational neuroscience and similar fields; mutlidisciplinary and interdisciplinary thinking is pushing the boundries” — Chris Corbishley & Nic Brisbourne, investors at Forward Partners

Sector 1: Healthcare — 60 AI suppliers

The involvement of AI in the medical industry has the potential to provide some of the biggest changes in our everyday lives — future global impact of AI on healthcare is estimated to be $200bn-$300bn. Utilising machine learning and data analysis to improve diagnosis, research and treatment is becoming a big trend in the development of AI around the world.

Babylon Health’s goal is to make affordable health services accessible to all, by providing a platform from which users can access healthcare professionals and triage services (an assessment of the urgency at which a wound or illness should be treated). Babylon has utilised AI in conjunction with the expertise of professionals to produce a chatbot which boasted a 92% accuracy in triaging patients.

BenevolentAI aims to improve natural science research. Their AI is using meta-data from academic papers to radically improve the efficiency of drug development, although their activities aren’t just limited to healthcare. BenevolentAI is utilising a similar process throughout science to increase the yield from scientific papers, expanding the amount of useful information available to scientists and industry.

Kheiron Medical Technology is a company whose sole aim is to use machine learning software to improve radiology in order to support the diagnosis and treatment of cancer, particularly breast cancer. In a recent study commissioned by the company and reported in the Economist, Kheiron’s software exceeded the officially required performance standard for radiologists screening for breast cancer.

Sector 2: Fintech — 140 AI suppliers

“London has been a global centre for quantitative finance for decades with a vibrant ecosystem of top talent working at large banks, asset managers, hedge funds, financial technology companies and regulators.” — Doron Reuter, ING Wholesale Banking

Financial technology is, unsurprisingly, one of the premier sectors in the London AI ecosystem. Fintech received $1.3 billion in venture capital in 2017–20% of London’s AI VC investments that year and the largest percentage of any sector we highlight in this article. With 140 Fintech firms in London and the potential global impact of AI on the financial sector estimated to be $200–300bn, Fintech is fully geared up to be the driving force for growth not only for London but for the entirety of the UK. Companies in London are changing personal finance, venture capital as well as portfolio-based investment by providing key insights and opportunities only made possible through the use of artificial intelligence.

Cleo is the pioneer in personal finance management. Its intelligent programme analyses transaction data using the world-leading financial software SaltEdge, then uses a custom AI brain to analyse spending trends and habits to let people spend smarter and keep track of their budgets. The company’s goal is simply to help people manage their spending better.

ACORN Machine (previously Oak North) provides a platform (ACORN) which addresses the challenges faced by small and medium-sized businesses in acquiring fast and bespoke lending. ACORN leverages big data and machine learning to provide analysis, monitoring and portfolio management to lenders to minimise risk and enable lenders to make smart decisions in a shorter timeframe than the commonly used “checklist driven approaches” would allow.

Heckyl operates in the space of information analytics for worldwide financial markets. Heckyl collects, analyses and presents global news and market data through their platform which allows investors to leverage more information than that which would normally be available to them, in order to make smarter investment decisions.

Sector 3: Sales and Marketing — 200 AI suppliers

The future global impact of AI-based innovation in sales and marketing has been valued at $1.4tn to $2.6tn by the McKinsey Global Institute, which is the largest global impact of any London-based AI sector, highlighted by the Mayor of London’s 2018 AI Report. This huge monetary impact is indicative of the fact that, according to WARC, half of brands and 58% of agencies in the UK and the US do not think they currently have the marketing tools they need. This would suggest that AI has the potential to fill the gap in terms of tools to deliver tangible value in the marketing space. As such, 86% of marketers and 96% of experts participating in a Forrester Consulting study stated that AI will make marketing teams more efficient and more effective, therefore it’s highly likely that firms will invest into AI to improve marketing strategy especially as 40% of brands and agencies expect their budget to increase in 2018 by an average of 10%.

Qubit is a company who optimises websites using a data-driven approach. The idea is that each person visiting a website is unique — with unique reasons for visiting and motivations to buy. As such, Qubit collects over 120K events per second to deliver over 1 billion personalised experiences per day, so that Revenue Per Visitor (RPV) can be maximised (up to 14x according to the company).

Fospha incorporates multiple customer touchpoints into their business model. In the wake of multi-channel marketing as dominated by Google and Facebook, Fospha aims to deliver on one key metric integral to any form of multiple channel marketing success: understanding and optimising the cost of customer acquisition.

Codec focuses on improving a fundamental process necessary for effective marketing — customer segmentation, specifically to optimising content creation. The company provides an AI powered cultural segmentation platform and consumer insight tool, which allows brands to discover new audiences, and effectively integrate and activate them through their content strategy.

Section B: Supporting Institutions

“What makes London great for AI? Three things. (1) World-class universities in AI. (2) The UK has a historic pedigree in science and engineering. (3) A melting pot of industries ripe for transformation.” — Daniel Hulme, CEO at Satalia

As AI is an emerging technology, the full potential of our industry is yet to be seen. New capabilities are going to be forged in academic and entrepreneurial spheres alike. As such, the significance of institutions such as universities and non-governmental research centres to the growth and development of AI cannot be understated. This is particularly pertinent in London, as the most common theme in our discussions with active members of the ecosystem was a high regard for the impact of the world-class universities in and around the City and the Alan Turing Institute (ATI).

“The key to London’s success comes down to a delicate balance of large corporates, SMEs, global research universities and enlightened government. Inputs such as highly skilled machine learning and development talent, patient capital, and an inquisitive market of early adopters were critical.” — Chris Corbishley & Nic Brisbourne, Forward Partners

As such, we’re going to highlight the key universities developing the best AI talent, the leading institutions which aid in leveraging that talent for research and finally mention the Venture Capital firms who are fueling the London AI engine with much needed capital.


“We cannot understate the importance of UCL’s computer science department or the proximity to several other world class faculties.” — Azeem Azhar

Imperial College London’s Department of Computing boasts 16 research groups and 5 research centres under the umbrella of Artificial Intelligence. The department operates a ‘research network’ called AI@Imperial, which “brings together experts across engineering, science, healthcare and business to develop AI methods and systems” focusing especially on the themes of Machine learning and AI for healthcare.

University College London is among the five founding universities of the Alan Turing Institute and its Computer Science Department, home to an AI research group and an AI research centre, was ranked highest in the UK for research. The University’s Centre for Artificial Intelligence, sponsored by the likes of DeepMind, Adobe and ASI, has been the soil from which multiple AI companies such as bloomsbury.ai and braintree.com have sprouted.

Queen Mary University of London is yet another one of the universities who founded the Alan Turing Institute. The university has a particular pedigree in image/video forensics and analysis and as such Queen Mary has invested in two supercomputers (IBM’s POWER9 system) to supplement its activities in this field. Additionally, QMUL founded The Game AI Research Group at the end of 2017, to use “games as a test-bed for and an application of advanced artificial intelligence (AI) methods”.

Non-Governmental Organisations

The Alan Turing Institute, headquartered in the British Library in London, was created as the national institute for data science in 2015 and in 2017 became a centre for research on artificial intelligence as a result of a government recommendation. The Engineering and Physical Sciences Research Council (EPSRC) founded the institute in conjunction with the universities of Cambridge, Edinburgh, Oxford, Warwick and UCL. Since its inception, the EPSRC has invested £42 million into the institute in total which has paid great dividends as multiple key members of the ecosystem noted the institute as a prominent figure not only for AI in London but for AI research globally.

The British Computer Society was established in 1957 and holds the mandate of “making IT good for society”. The BSC is foremost a hub for IT education — providing qualifications and professional certifications in the UK and internationally, however, their activities include writing articles and newsletters, running specialist events, supporting charities like the Turing Trust and creating international advisory committees. Areas the BSC aims to affect include education, healthcare and personal data protection.

The Charity Aid Foundation (CAF) is a UK based “bank for charities and not-for-profit organisations”, with offices in London and West Malling. The CAF provides accounts tailored to the needs of charitable organisations but also engage in activity to supplement the philanthropic activity of their clients. They have provided policy advice to “The House of Lords Select Committee on Artificial Intelligence” concerning the relationship between AI and NGOs — they stress that AI is likely to help charitable organisations achieve their goals but will create new ethical challenges as the technology emerges. The CAF has proposed that these ethical challenges could be overcome with the help of the same charitable organisation utilising the technology.

Venture Capital Firms

Octopus Ventures is one of the largest and most prolific VC firms in Europe who specialise in early-stage investments. Considering the relative youth of the London ecosystem, it’s then no surprise to find them included in this snapshot. Octopus has garnered attention after investing in three UK-based AI companies — natural language processing company Evi Technologies, predictive keyboard software company Swiftkey and AI video start-up Magic Pony, which were later sold to US tech giants Amazon, Microsoft and Twitter respectively. Alongside their investment activity, the company recently released a promising report on the global (and UK) VC industry.

MMC Ventures has a wide portfolio of AI companies, 12 to be exact, and these companies range from expertise in customer services, food delivery, marketing and data analytics. As of late, MMC has been very active in supporting its existing portfolio members. Just this month Peak — a software developer within the MMC portfolio, released an AI Platform-as-a-Service (PaaS) after securing Series A investment from MMC and Praetura of £5m. Additionally, MMC aided German insur-tech startup Omni:us, secure €19.7m ($22.5m) in funding this year.

AI Seed, as the name would suggest, specialises in funding and supporting early-stage AI startups. Although notably smaller than the other funds we’ve included thus far, AI Seed is taking a unique approach to VC activity which could pay great dividends in the future considering the relative adolescence of the firms in the ecosystem. Their strategy is built around supporting up to 20 ML/AI startups a year with a £100,00 investment for a 5–10% equity stake. In conjunction, AI Seed offers pre- and post-investment support tailored to the specific needs of their AI/ML target demographic. They currently have 27 firms in their portfolio.

Section C: Community

“In the early days, organisations such as Pivigo and ASI Data Science pioneered the challenges of getting AI and machine learning talent out of top universities and into companies to help them bring a data-driven approach to their operating models.”- Chris Corbishley & Nic Brisbourne, Forward Partners

All the infrastructural advantages and features of London mentioned thus far would be far less of a benefit without the right community to back it. Without London business acumen leading to relationships and clusters forming, it’s conceivable that the fertile soil in the British capital could have fostered a fraction of the AI success that we see today. More specifically, the synergies that were formed between academia and business were noted by insiders as one of the major factors contributing to London’s success in developing and implementing AI.

“I’m seeing a cultural change, especially around the development of the entrepreneurial ecosystem, as well as more effective links between industry and academia, which accelerates AI innovations to market.” — Daniel Hulme, CEO at Satalia

In this vein, we’re going to give you some entry points into the community, some people to look out for and some places that our AI compatriots like to meet!


General Tech Entry Points

Silicon Roundabout — 13,124 members. Is the ideal place for tech entrepreneurs, developers, and professionals in London to meet, share ideas, and connect. Their mission is to help innovators develop new technologies and convert their innovations into real business success. Meetups run Monthly (occasionally twice a month).

London New Tech — 14,574 members. Meet monthly to showcase new technology from London and around the world. The idea is to promote new technologies to tech-interested public, as well as potential clients, employees and investors. Additionally, they aim to provide inspiration and networking opportunities to those who want to find their passion and pursue what they love. Meetups run Monthly.

Technopreneurs — 12,110 members.A group of IT professionals, web startups and entrepreneurs. This group is for all those who not only want to become part of a meetup but also want to speak and participate. Meetups run Monthly.

AI Specific Meetups

Data Science London — 8,527 members.The largest data science community in Europe. A community of data scientists, data geeks and data hackers that meets regularly to discuss data science methods, topics, tools & technologies. It promotes free and open dissemination of data science knowledge. Meetups run Monthly.

London Machine learning — 6,891 members. A group of like-minded developers and scientists interested in Machine Learning, Probabilistic Graphical Models and Natural Language Processing. This meetup hopes to bring together machine learning practitioners to listen to each other’s work. Meetups run Monthly.

Big Data Developers in London — 7,096 members. An IBM sponsored meetup group geared towards developers, data scientists, data engineers, and all Big Data enthusiasts. Meetups provide an opportunity to learn, to work hands-on with the solutions and tools, and to interact and share knowledge with experts at IBM. Meetups run Monthly.


These influencers were highlighted by our ambassadors both for their visibility and activity online as well as their contributions to the local ecosystem. Check them out!

Ian Hogarth

Is a Cambridge graduate, engineer, successful entrepreneur and is an angel investor in about 30 start-ups. He gives talks to AI researchers, investors, politicians and policymakers, and runs a blog at: www.ianhogarth.com. Twitter: @soundboy

Libby Kinsey

Is a ‘smart generalist’, a Venture Capitalist specialising in Machine Learning and AI and Co-Founder of Project Juno in London. She has a wealth of experience in venture capital but nevertheless managed to pick up a ML degree along the way. Twitter and Medium: @libbykinsey

Azeem Azhar

Is a strategist, product entrepreneur and analyst. He curates ‘The Exponential View’ (http://www.exponentialview.co/), sits on the editorial board of the Harvard Business Review and is the Senior Advisor for AI to the CTO of Accenture. Twitter: @azeem

Rob McCargow

Director of AI at PwC UK, Rob is a self-described “evangelist for responsible technology” and as such is an advisor to the All-Party Parliamentary Group on AI and also to The IEEE Global Initiative for Ethical AI and a TEDx speaker.

Twitter: @RobMcCargow

Hal Hodson

Is the technology correspondent at The Economist. Hal has written about internet policy, economics, robotics, AI and infrastructure for the New Scientist, and did freelance work for The Guardian, The Independent and COSMOS. Twitter: @halhod

We thank you for the time you took reading this article and hope it was useful to Londoners both new and old. Check out other interesting publications such as newsletters, weekly must-read lists and ecosystem articles on the City.AI medium page and other channels.

For more information about AI activity in London and news regarding events run by and for London AI practitioners please contact the London chapter of City.AI — london@city.ai.

Written and Edited by Sebastian van Eerten

Special thanks to the Ambassadors of the London City.AI Chapter — Catalina Butnaru, Jamie Qiu, Rodolfo Rosini & Maria Diaz

Applied Artificial Intelligence

Making knowledge on #AI accessible

Sebastian van Eerten

Written by

Currently a student at the University of Amsterdam and content lead for City.AI. I am inspired by human progress & am a proud member of #appliedAI nation.

Applied Artificial Intelligence

Making knowledge on #AI accessible

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