Welcome to The Circuit series. Meet our next interviewee:
Most known for its cloud computing technology, Amazon Web Services (AWS) has also carved out a vital position leveraging its vast resources to support new generations of startups and scaleups.
Whether it is technical advice, strategic programmes or resource sharing, AWS has provided a diverse range of firms with the critical support needed to grow. Among the company’s top figures working towards this end is Tricia Troth, head of startups in the UK & Ireland at AWS.
In this exclusive interview, Troth discusses the work of AWS in supporting startups and what she has learned about the UK’s ecosystem of tech companies from her position.
What role does AWS play in supporting UK startups?
AWS supports UK startups with an unparalleled AI stack, expert technical advice, go-to-market support, and strategic programmes designed to help them scale and grow.
We offer venture expertise and interlock with investors to help startups fundraise, and through dedicated go-to-market support, the AWS Partner Network and Marketplace, we also help startups to expand their products and services to new markets, capture potential customers and generate business leads.
Over the last 20 years we have helped more startups launch, build, and scale than any other cloud provider, including UK success stories such as Deliveroo, Monzo, Starling Bank, Synthesia, and Zilch.
Why is it important for large firms like AWS to work with earlier-stage businesses?
If we don’t support these early-stage companies to scale, Europe loses its competitive advantage.
To support this thriving sector to continue to innovate and compete on a global stage, firms like AWS have an important play a role in helping early-stage startups to take full advantage of digital technologies.
With 70+ state-of-the-art services for data analytics, AI and machine learning fine-tuned over two decades of experience, AWS has the broadest and deepest solution set to help UK startups make better decisions faster and create outstanding generative AI applications.
Our scale and partnerships with thousands of VCs, incubators, accelerators, co-working spaces, universities, and others, also helps to ensure startups get the guidance, support, and infrastructure they need to build disruptive businesses.
One example is Tech Nation’s London AI Hub, of which AWS is a founding partner alongside Merantix Group, Husayn Kassai (founder of Onfido), and Techspace.
This public-private partnership unites AI entrepreneurs, researchers, and industry leaders to shape the future of AI through community, coworking and impactful events, in one dedicated space.
Inspiration can come from anywhere, but it takes more than an idea for startups to succeed. That’s why we also offer global support programmes like AWS Activate, which help early-stage businesses to get off the ground with business and technical expertise, and credits to test and start building solutions with little to no upfront costs.
Since its inception in 2013, AWS Activate has provided more than $8bn in credits and helped more than 350,000 startups across the globe. This includes UK startups such as Olio which has leveraged the programme to develop its app on AWS to cut down on waste by allowing people to share surplus food and unwanted household items.
What have you learned about the British startup ecosystem from your work at AWS?
UK startups are blazing the trail in AI adoption and are embedding the technology deeply into their businesses to gain competitive advantage from the outset.
According to Unlocking the UK’s AI Potential, a report by Strand Partners commissioned by AWS, AI adoption in the UK has grown by 33% in the past year, outpacing the European average (27%).
While large enterprises are experimenting with AI to make surface-level efficiency gains, startups are embedding AI deeply within their processes or build completely new products and services.
I’ve seen this first hand with UK startups like BeyondMath which provides a generative physics platform for physical world simulation, built on the market’s largest AI model for real-time industrial scale engineering.
The company uses AWS’s compute and AI services to scale training and inference of its AI models, support rapid experimentation, and deliver fast and reliable physics predictions for customers like Formula 1 teams.
Another example of a startup that has embedded AI into its business operations is Motorway, the fastest growing used car marketplace, which uses AWS’s AI services such as Kiro and Amazon Q for code development to make it easy to write new features and functionality, to understand design decisions, and quickly onboard new engineers.
To continue accelerating the UK’s AI adoption and support startups, the UK must continue to foster its already vibrant funding ecosystem and build on its current position as a leader in European VC funding.
Our research shows that access to funding is a key enabler for startups in their adoption of AI and their business growth.
Nearly half (48%) of startups said that VC and funding options have been one of the most important enablers of their growth. 88% of businesses reported that government support (e.g., grants) is important in their decision to adopt AI technologies.
How has the advent of generative AI affected AWS’s work with UK startups?
Generative AI is the most transformative technology shift in how we interact with data and each other we will see in our lifetimes and beyond. UK startups are transforming industries using AI.
For example, UK startup Fabacus is disrupting the retail and brand/IP licensing industries by supporting companies like Tesco and Hasbro to achieve more with their data.
Fabacus built an agentic AI engine using Amazon Bedrock and Anthropic’s Claude that transforms how executives access critical business data—replacing hours of manual analysis with instant natural language queries, cutting time-to-insight by 70% and redirecting 25% of operational capacity toward revenue-driving activities.
We are excited about our momentum with generative AI startups and will continue to focus our efforts on supporting these founders.
Just as AWS democratised access to cloud computing services, AWS has democratised access to building and using generative AI technology so that companies of all sizes, and across all industries, and developers of all skills sets can take part in this transformation to grow their businesses.
To further support startups to drive innovation with generative AI, we also launched new programmes and investments.
This includes a $230m commitment for startups around the world to accelerate the creation of generative AI applications and the AWS GenAI Loft London which for the last two years has provided a one-stop destination for in-person engagement for startups and developers to learn how to use and implement generative AI technology, get up to speed on the latest trends, and connect with a wider community of technology and business experts.
We also launched the AWS Generative AI Accelerator, which has helped many UK startups such as Latent Labs, PhysicsX, and Odyssey.
What qualities tell you that an AI startup has real potential?
We are now at a stage where virtually all startups will be applying generative AI to their business in one shape or form. For our 2025 AWS Generative AI Accelerator we honed our focus to support those startups developing the foundational technologies that will define what’s possible with AI.
For example, those that are exploring fine-tuning open-source models, pre-training foundation models (FM), or providing critical services in the emerging generative AI tech stack that surround the FM with data preparation, model monitoring, infrastructure provisioning.
For example, a British company that took part in the 2025 cohort was Inephany, which helps machine learning teams train models much faster, cheaper, and more effectively by providing them with AI-powered optimisation solutions.
The startups we selected for the programme had validated their solution through early enterprise pilots, beta users, or signed contracts—and are actively working toward compliance, security readiness, and operational scale. We also looked for startups that had demonstrable revenue and customer growth, and funding traction, as well as a founding team with proven AI/ML expertise.
