ScienceMachine, a British AI startup accelerating BioTech data analysis with a fully autonomous agent, has raised a €2.9 million pre-Seed funding round to support product development and hiring, particularly in sales and pharma partnerships.
The round was led by Revent and Nucleus Capital, with participation from Juniper and strategic angels.
“Our goal is to help biopharma make groundbreaking discoveries faster and cheaper,” says Lorenzo Sani, CEO and Co-founder of ScienceMachine. “Our AI agent works around the clock, analysing research data from lab to clinic, turning raw data into breakthroughs in hours, instead of months. And we are only at the beginning. We feel like AI will truly transform research and discovery in the coming years.”
Founded in 2025, ScienceMachine is building AI agents that transform how BioTech and pharma companies analyse data and make discoveries. Its flagship product, Sam, acts as an always-on AI bioinformatician, helping scientists extract insights from their research faster, more accurately, and at lower cost.
The company’s autonomous AI agent, Sam, functions as a 24/7 AI bioinformatician, automating the entire data analysis pipeline for BioTech and pharma companies and enabling faster scientific discovery.
With a team of just two, and by automating internal work with AI, ScienceMachine claims to outpace teams 100 times their size, launching a fully autonomous AI agent that is already in use by BioTech customers. Without marketing spend or a sales team, the duo delivered “what many larger players have not yet achieved“: production-level AI automation that reduces cost and accelerates scientific discovery.
Rebecca Brill, Principal, Revent, said: “ScienceMachine is one of the most impressive examples we’ve seen of pure execution. With just two people, they’ve built a product that’s not only best-in-class technically, but already delivering measurable value to customers. They’re perfectly positioned to disrupt one of the largest and most important markets in the world.”
ScienceMachine reportedly solves a problem that severely slows down biomedical progress today: Research teams in the life sciences face an overwhelming flood of complex biological data from labs and clinics but struggle to hire enough data scientists, a key role for them. In parallel, domain experts often lack the time or training to run sophisticated BioTech analyses. As a result, the company says many discoveries are delayed, or missed altogether.
AI agent Sam looks to close this gap: It integrates directly with existing databases and lab workflows, then continuously processes experimental data to find patterns, insights, and potential breakthroughs – without any manual intervention. In effect, Sam provides researchers with the same output that would normally require an entire team of data scientists, significantly accelerating their work.
Sam handles everything from data cleaning to exploratory analysis to visualisation, continuously and autonomously unlocking faster research cycles and reducing the cost of discovery.
Early customers report results in a third of the time, at a fraction of the price, and of a higher quality than they could have achieved on their own.
Maximilian Schwarz, General Partner, Nucleus, said: “We believe that agentic architectures will become the dominant interface for scientific software. ScienceMachine is ideally positioned to dramatically expand access to complex bioinformatics for wet-lab scientists and speed up iteration cycles, ultimately increasing the addressable market and accelerating R&D timelines.”
One month after launch, ScienceMachine already has multiple contracts and a fast-growing pipeline without spending a cent on marketing.
The funding will support product development and hiring, particularly in sales and pharma partnerships.
ScienceMachine plans to expand its reach from BioTech startups into larger companies – where ACVs are higher and the need for scalable, flexible data automation is even greater.
Michael Luciani, General Partner, Juniper, said: “Ben and Lorenzo have the fastest speed of execution of any team we’ve met in this space, the most nuanced understanding in how to go to market and scale, and the most well-thought-out product we have tried, all of which are what we believe key to success in this field.”
Read the orginal article: https://www.eu-startups.com/2025/07/london-based-sciencemachine-raises-e2-9-million-for-biotech-analysis-with-a-team-of-only-two-and-without-spending-a-cent-on-marketing/
