Participated · Series C · Jul 2026

Spun out of the University of Oxford in 2017, Moa Technology operates proprietary discovery platforms that have screened over 900,000 compounds and discovered more than 80 novel mode of action areas capable of breaking weed resistance. Several of its advanced programmes are now in their third year of international field trials, and in 2025 the company disclosed a new category of non-herbicidal products called Moa Amplifiers. Moa has established R&D collaborations with major industry partners including Nufarm, Gowan, Certis Belchim and Corteva Agriscience to progress commercial applications. The company plans to use its Series C proceeds and partner payments to push three lead programmes closer to commercialisation, expand its early-stage pipeline, and continue development of the Moa Amplifiers strategy. Its platform and commercial partnerships are positioned to support further industry deals and field deployment of its discoveries.

Participated · Seed · Nov 2025

Scripta Therapeutics combines experimental biology with artificial intelligence and advanced imaging to create and modulate disease maps based on transcriptional networks. By analysing patient-derived cellular models, the platform identifies nodes that can be targeted to shift diseased cells back to healthy phenotypes. Although broadly applicable, the company’s initial therapeutic focus is on Alzheimer’s disease and other neurodegenerative disorders, developed in collaboration with co-founder Professor Noel Buckley of the University of Oxford. The approach integrates wet-lab experimentation and computational analysis, positioning Scripta at the intersection of drug discovery and precision medicine. The recent seed financing provides $12 million of runway to expand operations and accelerate development programmes. No commercial products or revenue figures have been disclosed to date. The company’s leadership is headed by founder and CEO Peter Hamley, and its board now includes Ray Barlow as a non-executive director.

Participated · Series A · Oct 2025

Founded in 2021 as an Oxford University spin-out, Wild Bioscience combines evolutionary biology, machine learning and precision gene editing to improve the genetics of staple crops. Its platform mines hundreds of millions of years of plant evolution to pinpoint desirable traits from wild species and introduce them into modern elite varieties. The company’s 30-person team operates from its Oxford headquarters and is already running field-trial programs in four countries, reporting early successes that it aims to turn into commercially available seed. Wild Bio targets improved crop productivity, enhanced climate resilience and broader agricultural sustainability, addressing global food-security challenges. The firm frames its approach as complementary to, yet distinct from, the AI analytics and robotics tools dominating many AgTech investments. With fresh capital in hand, management plans to expand R&D capacity, scale commercial operations and bring its first seed varieties to market. The recent €51 million Series A positions Wild Bioscience among the largest early-stage AgTech financings in Europe this year, underlining strong investor confidence in its science-driven model.

Participated · Series C · Jul 2025

Ultromics, spun out of the University of Oxford, offers EchoGo®, an artificial-intelligence platform that turns routine cardiac ultrasounds into objective diagnostic reports. The system is trained on one of the world’s largest echocardiography datasets and validated against actual patient outcomes, enabling it to identify subtle markers of HFpEF that are frequently missed in standard workflows. EchoGo has already analyzed more than 430,000 echocardiograms and is deployed in hospitals across the United States and the United Kingdom. Clinical studies cited by the company show the software reached a diagnostic decision in 93% of patients versus 40% for traditional HFpEF risk scores, with consistent accuracy across gender, age and risk groups. Ultromics’ technology is reimbursed by public and private payers and is cleared by the U.S. FDA, underscoring its commercial readiness. Backed by multiple investors and health systems, the company aims to make early identification of heart failure a standard part of cardiac care worldwide.

Participated · Equity · Oct 2024

Diffblue, founded by researchers from the University of Oxford and based in Oxford, England, builds reinforcement learning–powered AI tools to automate unit test generation. Its flagship product, Diffblue Cover, autonomously generates unit tests that are guaranteed to compile and pass while delivering high coverage and test strength. The company combines reinforcement learning with code execution to refine outputs, reduce hallucinations, and improve accuracy versus traditional LLM approaches. Diffblue says Cover can write unit tests up to 250x faster than a human developer and is used by customers including Citi, ING, Workday, S&P Global, and BNY. Through participation in the ITEA GENIUS project, Diffblue plans to develop tools and processes to automate complex software-engineering tasks, improve software quality, and accelerate development cycles. The company recently received a £1 million grant from Innovate UK to accelerate enhancements to its reinforcement learning–powered solutions for autonomous test code generation. Diffblue builds Diffblue Cover, an autonomous generative AI-for-code product that automates unit test generation using reinforcement learning techniques rather than LLM-based coding assistants. The company says this differentiated approach helps avoid accuracy, security, privacy, and liability concerns associated with LLMs. Diffblue Cover aims to improve code quality, expand test coverage, and increase engineering efficiency so teams can ship software faster and with fewer defects. Today Diffblue serves four of the 10 largest U.S. banks and several other members of the Forbes Global 2000; customers include Citi, ING, Cisco, AstraZeneca, and BNY Mellon. The company is led by CEO Toffer Winslow. Diffblue intends to use the new funding to expand operations and accelerate development of its product. Diffblue provides autonomous AI-for-code software that helps software teams improve code quality, expand test coverage and increase productivity. The company, led by CEO Mathew Lodge, offers a newly launched version that can autonomously write and maintain unit test suites for entire applications and automatically refactor Java code to improve testability. Its solution also slashes the time and cost to run tests in continuous integration and helps development managers understand test coverage and code risk across their organization. Diffblue raised $8M in funding and intends to use the proceeds to expand operations and broaden its business reach. The company is based in Oxford, UK. Diffblue is a University of Oxford spin-out that applies artificial intelligence to software development, built on ten years of academic research. Its core AI builds an exact mathematical model of a codebase from a few examples to achieve deep semantic understanding of programs. Diffblue is initially developing three products on that engine: an automated testing tool that spots bugs and writes tests, a security product that flags exploitable bugs and generates tests, and a refactoring product that rewrites outdated or poorly expressed code. Founder Daniel Kroening, a Professor of Computer Science at Oxford, says the longer-term vision is for the system to be able to write entire programs from examples. Financially, the company recently raised $22 million in a Series A led by Goldman Sachs Principal Strategic Investments, one year after leaving academia. Diffblue’s stated thesis is that AI augmentation or replacement of software developers is necessary to meet growing demand for software.