For centuries, scientific discovery has run on the same loop: hypothesize, experiment, interpret, repeat. We're building AI systems that run that loop autonomously — compressing decades of progress into years.
The companies that make meaningful contributions to scientific progress won't just sell research copilots. They'll be AI-native discovery engines that work alongside researchers to propose and validate hypotheses.
Xineplus exists to build those engines. We combine frontier generative AI, physics-informed neural networks, GPU-accelerated simulation, and multi-objective optimization into closed-loop platforms that autonomously discover drugs, materials, and proteins.
Frontier AI models now match PhD-level performance on scientific reasoning benchmarks. They can propose hypotheses, design experiments, and interpret results with expert-level sophistication.
GPU-accelerated physics simulations and neural network surrogates have made it possible to evaluate millions of candidates per hour — making brute-force exploration viable for the first time.
Automated labs, robotic synthesis, and high-throughput assays mean AI-generated candidates can be physically tested at scale — closing the loop between computation and experiment.
Our team combines deep domain expertise in computational chemistry, materials science, and protein engineering with world-class AI and infrastructure engineering.
Co-Founder & CEO
Leads company strategy, research partnerships, and the mission to make autonomous discovery accessible to ambitious scientific teams.
Co-Founder & CTO
Leads the AI platform, GPU infrastructure, and product architecture behind Xineplus closed-loop discovery engines.
Every prediction we make is grounded in physics and validated against experimental data. We don't ship hype — we ship accuracy.
Patients are waiting. The climate is changing. Every month we shave off a discovery timeline is a month the world benefits sooner.
Our platforms work alongside scientists, not around them. We augment human intuition with computational scale — never replace it.
Xineplus founded with $12M seed round. Core team assembled from DeepMind, Roche, Google Brain, and Genentech.
First closed-loop drug discovery campaign completed. 4-week target-to-lead cycle achieved with 3 pharma design partners.
XineMaterials and XineProtein launched in beta. Series A fundraise completed at $45M. Team grows to 60.
All three platforms available commercially. First self-driving discovery campaign runs fully autonomously from target to validated candidate.
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Total Funding
Products Shipped
Xineplus is based in London, UK, close to leading universities, biotech clusters, pharmaceutical partners, and deep technology investors.
Our London base gives research teams a European partner for AI-native discovery while supporting collaborations across North America, Europe, and Asia.
Headquarters
Co-Founders
Discovery Platforms
Researchers stay in control of campaign goals, validation decisions, and final interpretation.
Every recommendation must carry enough data for a scientist to inspect, reproduce, and challenge it.
AI engineers, domain scientists, and product teams work as one group around shared discovery outcomes.
Partnered with leading research institutions