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Creating a Smarter Future

Tech Nation's Applied AI companies


It’s no surprise that, when faced with the words ‘artificial intelligence’, most people immediately think of the word ‘hype’ shortly thereafter. The technology has been much anticipated, and although the term has been around since the 1950s, the general public is still waiting to see it have a significant impact on their lives.

Recent numbers from the MMC report showed 40% of European startups classified as “AI startups”, showed no sign of using AI. Despite all of this, where there is substance, investment in the technology is booming like never before.

Tech Nation is proud to support and represent 29 of the most exciting AI companies in the UK. These companies have undergone a rigorous judging process, to help you cut through the hype, get to the core of their product and see what they’re really made of. Read more about them and how they were selected.


Why is AI booming? 

As the sophistication improves and potential for the application of AI broadens, confidence in the technology has massively increased. To get a holistic view of how and where AI is thriving, let’s look at worldwide investment, which has skyrocketed since 2017 and shown no signs of slowing down. Possibly, 2019 could be a record year for AI investment.

$3.5bninvested in AI in 2014
$4.5bninvested in AI in 2015
$6bninvested in AI in 2016
$16.5bninvested in AI in 2017
$19bninvested in AI in 2018
$16bninvested in AI in 2019

**To compare, in the year of 2010, AI barely saw $1 bn in investment worldwide


How is the UK comparing?

Investment in the UK’s AI technology has grown almost six-fold in the last four years, but how does it compare to the rest of the world? 2019 has so far seen the following numbers:

$9bnin the US
$3bnin China
$1bnin the UK

How many AI companies do we have?

300+Chinese companies
3500+US companies
800+UK companies

How many people do they employ?

300+Chinese companies
3500+US companies
800+UK companies

Why are our companies special?

Tech Nation ensures a thorough selection process based on expert criteria and judging panel. This year, we had the pleasure of hosting Marta Krupinska, Head of Google for Startups UK, Volker Hirsch (partner at Amadeus Capital), Dame Wendy Hall, David Kelnar of MMC, Tabitha Goldstaub (Chair of the UK Government AI Council) and Dr Mike Short (Chief Scientific Advisor, Department of International Trade) amongst others, as judges.

Companies who make it through the judging process are selected for the Applied AI programme, a highly specialised, six-month-long sector-specific growth programme that aims to provide peer to peer learning, expert classes and a long-lasting network. Judges had the following comments about the process and companies selected:

Less artificial, more intelligent

The Applied AI programme is doing things differently. It specifically looks for companies that aren’t just using AI for the sake of it, but apply it to solve real problems for businesses and society, with recognition and focus on social responsibility and ethics. Our companies specialities range between diagnostics and prevention of cancer and medical conditions, reducing fake news and misinformation, tackling climate change and waste management, autonomous vehicles and road safety, reducing burnout and improving mental health and identifying pay inequality.


Our Companies

Enterprise Tech

Aiming to improve mental health in the workplace, customer service, the gender pay gap, online advertising and everything in between.


Diagnosing DVT and analysing blood for early detection of cancers - our HealthTech companies innovate in healthcare.

Industry & Manufacturing

Industrial Automation & Manufacturing combine AI with age-old industries to make production faster and more innovative.

Mobility & Autonomy

Instead of racing towards the dream of autonomous vehicles, our companies are making roads and transport safer and more reliable for everyone.


The media has more power than ever. Our AI companies combat astroturfing and fake news, in addition to customising the online world of content.


Other companies are applying AI to traditional sectors like agtech and fintech, innovating in sectors like HR and waste management.



Innovating preventative measures in healthcare


Founder: Oliver Armitage, CSO

Location: Cambridge

Year founded: 2015

Core area of focus: HealthTech

Previous backing: Endure Capital

In a nutshell: BIOS is a leading neural engineering startup, creating the open standard hardware and software interface between the human nervous system and AI. Improving the quality of life for millions of people affected by chronic disease, they combine applied materials, machine learning, software and neuroscience with the experience of surgeons, clinicians and patients.

BIOS’ solution: Current care for chronic conditions is manual, time-consuming, constant, and often relies on at least one, if not many, prescriptions. BIOS aim to make the care of chronic conditions seamless and easy for both patients and clinicians. Their model will deliver SaaS-type healthcare, with new prescriptions delivered via algorithms, and a process that will cut costs, increase efficiency and deliver a high level of personalisation.

USP: BIOS has a number of major differentiators which gives it a significant advantage over potential competitors: An incredibly talented multi-disciplinary R&D team, the largest PNS (peripheral nervous system) neural data set in the world, with proven AI models for analysing neural data, a very strong IP portfolio and proprietary neural interface hardware.

Goals for the next 12 months:

  • Overcome scaling pains
  • Raise further investment
  • Find talent 

Experience: Founders Oliver Armitage and Emil Hewage are technically credible and specialised in a rare blend of technologies. Oliver’s PhD was in BioEngineering and he is specialised in tissue interfaces and engineering materials. These materials allow technology to be fused with the body, and has already developed cutting edge patented tissue interface technology for BIOS. Emil studied computational neuroscience for his PhD research at the University of Cambridge. 

Traction: Winner of MassChallenge (London) in 2015 and successful completion of Y-Combinator in 2017. Bios was awarded significant grant funding, including Innovate UK, SBRI and i4i Connect. They secured major equity funding of over $4.5M and partnerships with UC London, University of Cambridge, New York University, Nvidia, Digital Health.London and IEEE. They own the largest PNS (peripheral nervous system) neural data set in the world with proven AI models for analysing neural data. 

Website | Twitter


Founder: Bhavagaya Bhaski, CEO

Location: London

Year founded: 2017

Core area of focus: HealthTech 

Previous backing: None

In a nutshell: C the Signs is an award-winning platform founded by doctors. Using artificial intelligence mapped with the latest evidence, the tool is used by Doctors to identify patients at risk of cancer at the earliest and most survivable stage of the disease. Covering the entire spectrum of cancer, C the Signs can identify which cancer(s) a patient is at risk of and, what test, investigation or referral they need in less than 30 seconds. The tool is currently being used by over 1000 doctors in the NHS and trials to date have demonstrated a 30x improvement in cancer detection rates.

C the Signs’ solution: Founded by two doctors, C the Signs is an award-winning digital tool that uses artificial intelligence mapped with the latest evidence to identify patients at risk of cancer at the earliest and most survivable stage of the disease.

USP: Covering the entire spectrum of cancer, C the Signs can identify which cancer(s) a patient is at risk of, and what tests, investigation or referral they require, all in less than 30 seconds. The tool is currently being used by almost 1000 doctors in the NHS and trials to date have demonstrated a 30x improvement in cancer detection rates.

Goals for the next 12 months

  • Growth
  • Internationalisation
  • New product launch

Experience: The C the Signs team consists of experienced clinicians, designers, data scientists, engineers and a psychologist.


  • Clinical study 2017 - 2018 (publication this year - 30x improvement cancer detection rates p<0.05).
  • 7 NHS CCG Contracts (over 2M patients- rolling out to a further 23 NHS CCGs Jan 2019 - 10M patients).
  • Over 25 third sector charity Partnerships. Registered Class I Medical Device, CE Marked.

Website | Twitter


Founder: Matthew Baker, CSO

Location: Glasgow

Year founded: 2016

Core area of focus: HealthTech

Previous backing: Mercia

In a nutshell: ClinSpec Dx use artificial intelligence to analyse blood for early detection of cancers and other diseases. They have developed the world's first cost effective blood test for the early detection of brain tumours. Studies have shown that their technology can bring savings to healthcare service providers as well as improved quality of life for patients.

ClinSpec Dx’s solution: ClinSpec Dx are pioneering a new spectroscopic method for blood serum analysis, allowing same-day detection and grading of a range of diseases, with first applications to brain cancer.

USP: Low cost, rapid diagnosis of brain cancer for the first time, using novel hardware that can improve patient survival and quality of life, whilst bringing savings to the health services.

Goals for the next 12 months

  • Complete clinical study of 600 patients in NHS Lothian
  • Begin large cohort clinical trial in multiple sites across the UK
  • Secure Series A investment to complete regulatory roadmap and to launch test into the market

Experience: The core team has a strong track record in scientific achievement and commercial realisation. They combine the experience of commercial and academic backgrounds in order to push the translation of this technology.

Traction: Preliminary results from their primary clinical study were recently published in Nature Communications. In Q2 2019, they made their first sale on novel hardware for non-clinical applications. ClinSpec Dx was awarded Innovation Award at the Scottish Life Sciences Awards 2019.

Website | Twitter


Founder: Fouad Al-Noor

Location: London

Year founded: 2016

Core area of focus: HealthTech

Previous backing: EF, AI Seed Fund

In a nutshell: ThinkSono is an ultrasound AI company. AutoDVT is the world's first software that enables nursing staff to detect 'deep vein thrombosis' (DVT). DVT is a blood clot in the leg and is considered the number one cause of preventable hospital death.

ThinkSono’s solution: AutoDVT solves the DVT diagnosis problem by allowing all healthcare staff to detect DVT in just 10 minutes. It eliminates the need for a specialist (e.g radiologist or sonographer). Since AutoDVT enables nursing staff and junior doctors to detect DVT, it offloads a huge burden on not only themselves but also reduces cost and improves patient outcomes at the same time.

USP: Worldwide, there are very few ultrasound AI companies. And currently, only ThinkSono has a solution to detect DVT.

Goals for the next 12 months

  • Carrying out clinical trials. 
  • Ensuring their technology is as robust as possible. 
  • Sign commercial deals with ultrasound companies. 

Experience: ThinkSono have a strong team of more than 20 members, including two technical founders (hardware and software), four machine learning staff (post-docs), radiologists, haematologists and emergency doctors. 

Traction: So far, ThinkSono has published a patent for AutoDVT and filed a new patent along with collecting the world's largest labelled dataset for DVT. They have letters of intent representing more than 50 hospitals and published a peer-reviewed paper at MICCAI conference. They are in formal discussions with the two largest ultrasound companies in the world (which represent 48% of the entire ultrasound market) and are ready to start clinical trials to show the efficiency of the technology at the end of 2019. 



Founder: Ben Holland, CTO

Location: Cardiff

Year founded: 2017

Core area of focus: HealthTech

Previous backing: - 

In a nutshell: Antibodies are a very successful and valuable class of drugs. But discovering and developing them into new drugs is a laborious and unreliable lab-based process. Antiverse discovers and optimises new antibody candidates faster, meaning only better targeted and further optimised candidates are included in expensive clinical trials. With the top-selling antibody bringing in sales of $19.9bn in 2018, the potential is huge.

Antiverse’s solution: By taking the discovery and optimisation process in silico, Antiverse take data about a target molecule, such as the structure or sequence, from a customer and return the sequences of novel antibodies that bind to that target. They also provide antibodies optimised to possess whatever other properties the customer requires. 

USP: Nobody else is offering antibody generation fully in silico. Rather than require discrete lab work for every project, Antiverse do the lab work up front to build and train a fully-developed model capable of generating and optimising antibodies. Once mature, their models will be able to perform the whole antibody discovery and optimisation process in silico, at unmatched speed and accuracy.

Goals for the next 12 months

  • Affordably and sustainably recruit more Machine Learning professionals.
  • Raise investment. 
  • Business/customer development, especially structuring of deals.

Experience: Co-Founder Murat has worked as a bioinformatician and software engineer. Co-founder Ben has an MEng from Oxford with a specialisation in Information Engineering, and has since worked extensively on mathematical modelling and neural networks.

Traction: Antiverse have generated new antibody sequences in silico, which are currently being tested by a major pharma partner. They are in discussions with another major pharma company about a potential licencing/co-development deal. They are working on a pilot project for a third pharma company, and have a Letter of Intent for another. 



Enterprise Tech

Innovating the workplace with AI


Founder: Elizabeth Clarke, CEO

Location: Manchester

Year founded: 2014

Core area of focus: Marketing & Advertising

Previous backing: -

In a nutshell: Dream Agility uses Machine Learning and Visual AI to manage every aspect of Google Ads. From using Visual AI to attribute rich data from images, to MLoD (machine learning on demand) to disrupt the agency relationship, pass on massive savings and increase uplifts.

Dream Agility’s solution: Creating Google ads can be time consuming, labour intensive and expensive. Dream Agility’s visual AI accurately processes thousands of images a day and produces the data required to process SKU, or that Google requires for its ads. Using Dream Agility’s software not only saves on time and man-power, but will lead to an increase in sales as a result of having more relevant accurate and consistent data. It also uses Machine Learning to make Google ads more effective, thus decreasing spend and increasing conversion.

USP: Agencies are diametrically opposed to the end advertiser in the use of MLoD . Using it to reduce the waste will impact on their revenues if they work on a percentage of spend model. Dream Agility allows users to get the maximum impact, all while decreasing spend, and it can be used alongside any other bidding tech without interfering with the suggestions it makes. It's the perfect partner tool.

Goals for the next 12 months:

  • Refining their visual AI product.
  • Overcoming market objections by agencies.
  • Achieving direct adoption from end advertisers
  • Completing a raise with the aim to scale at speed

Experience: Dream Agility’s Lead Data Scientist’s PhD thesis involved applied machine learning techniques in particle physics research. He was involved with the Higgs boson discovery at the CERN laboratory in Switzerland and has since gained experience using Machine learning applications with medical data to help improve decisions regarding cancer treatment. Elsewhere, Dream Agility have a team of proficient developers. The company was founded on the commercial brains of a CIMA qualified Economist with an MBA from Manchester and a Best Selling Flirting Expert who was instrumental in the flotation of a technology transfer company with a 400 patent portfolio for £50m who made FTSE 250.


  • The Fragrance Shop saw Christmas sales up 3.6% year on year, with online growth of 19.3% and a 28.7% uplift in Black Friday sales. 
  • Chemist Warehouse, Australia’s largest pharmacy group, cut Google Ads costs whilst at the same time increasing conversion value by 178% over their previous year’s performance. 
  • My Generator, Australia’s largest online collection of power generators, saw sales increase by 425% year on year. The impact was so great that it captured the attention of national television, all while reducing their Google AdWords spend (64% reduction).
  • Idle Man UK’s revenues went up 53%, ROAS improved by 138% YoY in December, and ROAS over all territories up 239%.

Website | Twitter


Founder: Steve Erdal, Director of Linguistics

Location: Gateshead

Year founded: 2017

Core area of focus: Customer service

Previous backing: North East Innovation Fund

In a nutshell: Wordnerds teach computers to understand language, make decisions and find actionable insights. Using AI and advanced linguistics, they are turning the internet into the world’s biggest focus group.

Wordnerds’ solution: Wordnerds is a Cloud-based SaaS platform. It gathers huge quantities of text data from social media, online reviews, survey and forum data, and customer service messages, to bring out the actionable insight so it is available at a glance to the user. It focuses on the structures and patterns of language as well as vocabulary, meaning stakeholders can cut through the noise and understand what consumers really feel.

USP: Traditional solutions tend to rely on n-grams (the "bag of words" model), where the only input of the AI is the presence of a word, and its physical proximity to other words, treating a word like a number and not picking up on human factors like misspellings, politeness or sarcasm. Wordnerds works with the structure and pattern of the language, rather than the vocabulary, creating a deeper understanding of their meaning, and a product that focuses on the end-user, and jargon-free customer communication. 

Goals for the next 12 months

  • Balancing ideas and focus to create the perfect product-market fit.
  • Getting their products in front of the right audience and people. 
  • Streamlining processes to prepare for scaling. 

Experience: Pete Daykin is a serial entrepreneur with 15 years' experience of running Web Development and Digital Transformation Agencies in the North East. Pete has a BA from the University of Cambridge. Angela Daykin has spent the last 15 years in Finance Director roles in technology companies. Steve Erdal is a writer, linguist and Product Owner at Wordnerds. After studying Corpus Linguistics during an MA at Newcastle University, Steve formed his own linguistics-led marketing business in 2014. He has produced a range of linguistics-based research for a variety of HE organisations, including Oxford, Edinburgh, Durham, York, Queen’s Belfast, Bath and Cardiff.

Traction: Wordnerds was born out of a Nissan hackathon, where the team’s solution beat dozens of UK and global competitors. This won them the right to develop their product and their brand. They now work with a range of organisations, creating ROI from improving their customer service. Their MRR has moved from £3.5k to 22k and continues to rise. In addition, they won a World Innovation Award at the World Rail Festival in Amsterdam.

Website | Twitter


Founder: William Ritchie, CEO 

Location: London

Year founded: 2018

Core area of focus: HR Tech

Previous backing: Ascension Ventures

In a nutshell: Chosen AI is a people analytics platform that uses advanced Natural Language Processing and Deep Learning to help employers identify and optimise the potential of their existing employees. They have built a global contextual skills knowledge base that connects with existing HR systems to generate predictive insights that help align people strategies to business strategies.

Chosen AI’s solution: Chosen AI has built a unique technology and data platform that uses Natural Language Processing and Deep Learning to identify people’s proven skills and the context behind where and how they acquired them, making it possible to understand that the same job title at different companies often involves learning and using entirely different skills. As opposed to existing solutions, Chosen AI’s big data approach also takes into account people’s entire employment history, rather than just analysing their current role. 

USP: Chosen AI uses advanced natural language processing to extract skills from existing employee data (CVs, cover letters, performance reviews, work) and a global contextual skills knowledge graph to predict skills where data is missing. Their approach ensures skills are always representative of the current situation and have complete employee coverage without the need for any employee input.

Goals for the next 12 months:

  • Building a repeatable and scalable enterprise sales process.
  • Scaling the team, specifically design, product, sales and data science
  • Customer education and content marketing

Experience: Chosen AI’s CEO Will Ritchie spent 4 years in Tech M&A as an investment banker, advising the corporate strategy of some of the best-known global tech businesses. Before founding Chosen AI, he successfully launched and scaled Joblift. Charis Sfyrakis, Chief Scientific Officer, has 10 years of experience in high-performance computing and big-data science. Ashleigh Otter (COO) previously managed the accelerator programme at Founders Factory, mentoring over 50 early-stage businesses on their growth. Dr Jeffrey Ng, Chief Scientific Advisor & Company Director, has a doctorate in Machine Learning and Computer Vision.

Traction: The team has spent the last 3 months doing intensive customer discovery to ensure they fully understand the end-user and value proposition of their technology. Off the back of these interviews, they’ve had interest for PoCs, without starting an active sales push. This includes a Fortune 500 FMCG, a Fortune 500 Pharma, a Fortune 500 Insurer, a 15,OOO person Italian FMCG and a Fortune 500 FMCG. 



Founder: Dr Zara Nanu, CEO

Location: Bristol

Year founded: 2017

Core area of focus: HRTech

Previous backing: None

In a nutshell: Gapsquare enables companies worldwide to track pay disparity, pay equality and pay gap data instantly and sustainably, building fairer workplaces and simpler processes around fair pay. Gapsquare offers AI insights around building an inclusive workplace, and moving pay gap and equality analytics in-house and within the control of the company

Gapsquare’s solution: Their flagship product, Gapsquare FairPay®, is an easy-to-use cloud based software as a service. It allows businesses and organisations to analyze and track pay disparity statistics and produce instant reports on equality and diversity data, ready to be presented to teams. Companies running their HR and Payroll data through their software get instant in-depth knowledge around pay gap and pay equality data, helping them to both comply with, and go beyond government regulations.

USP: Gapsquare offers an integrated approach to pay analysis, allowing organisations to continuously monitor their data around disparities and/or any potential legal issues which may arise. Their software embeds an equality and diversity narrative that would normally come through costly consultancy. Within the tool, you effectively have an on-demand consultancy service as well as the ability to embrace continuous monitoring.

Goals for the next 12 months

  • Rapid market takeover.
  • Ensuring AI insights are directed at the right level within organisations using the platform.
  • Bias and ethics in AI - both algorithms and data.

Experience: Gapsquare’s CEO, Dr Zara Nanu, is an expert on how diversity and inclusion can shape more dynamic and productive teams and a more engaging and empowering workplace. Chief Data Officer and Co-Founder Ion comes from a background in artificial intelligence and machine learning. The VP for Partnerships and Growth, Sian, has a background that spans both the corporate and third sectors, and their Chief Technology Officer, Ant Kennedy’s background spans from rapid prototyping, growth engineering and architecture to transitioning ML research to client-facing products.

Traction: Gapsquare have had traction with large customers including Serco, Babcock, London Mayor’s Office, IDC and London Metropolitan Police have also signed a 3 year commitment. Their sales channels are law firms, and large software providers of HRM such as Oracle. They have over 30 organisations signed up to their platform and performing pay gap analysis/equal pay audits.

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