Founder building in healthcare. Cambridge medic in between.
4th year medic at Cambridge, running a stealth healthcare AI startup. Previously co-founded Marksy and Clerkr. The plan is to keep starting companies, ideally ones that change how healthcare and technology actually work.
Medicine, mathematics and technology are the three things I keep coming back to. I'm a fourth-year medic at Cambridge, with an intercalated year in Mathematical Genetics and Bioinformatics in the middle of the degree. I find the quantitative layer underneath medicine more interesting than most people in the field seem to, and the clinical layer more interesting than most people in the quant world. The overlap is where I want to spend my career.
I've co-founded two companies so far: Marksy (school assessment analytics, wound down with traction in 12 countries and a Department of Education trial in the pipeline) and Clerkr (healthcare AI for GP clinics, cut consultation times in half, onboarded GPs covering 10,000 patients within two weeks of beta launch). Currently running a third, in stealth.
Outside of building, I spend a lot of time picking up new maths topics for fun. Same with chess. I'm also trying to get into League of Legends more, less for the game itself and more for the kind of thinking it seems to build. Send me recommendations across any of these if you have them.
2026, ongoing
Rebuilding the clinical layer of modern healthcare.
Specifics stay under wraps for now. What we'll say is it's structural rather than cosmetic, and the timing is right.
If you're a VC and this resonates, reach out. We're not actively raising, but the right relationships are worth building early. We're selective: we care about genuine domain expertise, networks that open real doors, and partners worth growing with over time. Capital alone doesn't move us.
Sep 2025 to Mar 2026
Assessment analytics for secondary schools. Marksy took scanned or photographed exam scripts and turned them into structured performance data in minutes instead of weeks. The marking was the front door; the real product was the analytics layer sitting on top of it.
Question-level analysis, specification heatmaps, cohort breakdowns and score distributions, all generated automatically for every paper. Most schools wait two or three weeks after a mock for meaningful insight; we got that under twenty minutes. By the time we wound it down we had traction in 12 countries and a committed Department of Education trial in the pipeline.
Sep to Dec 2026
A healthcare AI agent for private GP clinics. Clerkr prepared the full clerking note for each patient before the appointment started, so the consultation itself could focus on the conversation instead of the keyboard.
In early use, 20-minute consultations were running closer to 10. Within two weeks of launching the private beta we had onboarded GPs covering roughly 10,000 patients between them.
Markets started for me in 2020. I was reselling sneakers, PlayStation 5s, Xbox Series consoles and GPUs into the pandemic shortages, then rolled the profit into NFTs early in that cycle. Some of those positions returned more than 100x at the peak.
After that I wanted something more systematic. I spent a few months building a Python research stack for crypto futures: a low-latency market-making engine with exchange connectors, an order book reconstructor, and a quote engine pricing off short-horizon microstructure features. On top of that, a pipeline of gradient-boosted models (XGBoost) over funding rates, on-chain flows and order-flow-derived signals, with walk-forward validation and a regime-aware portfolio layer.
The basket settled at an out-of-sample Sharpe above 1.2 net of fees. It was a one-off project, not something I actively run today, but the discipline behind it stuck. Strict data hygiene, honest cost models, and the assumption that anything that looks free probably isn't.
Long-form writing on things I've learned the hard way, plus a place I'll eventually post my thinking on where healthcare AI is heading.
Medicine, mathematics, and technology are the three things I keep coming back to. I think their intersection is where some of the most important problems of the next fifty years actually get solved, and I want to be someone working on them.
That comes partly from luck. The school I went to, the university I got into, the people I met along the way, none of it was purely down to me. I'm aware of that, and I think it comes with a responsibility to do something real with it. Not guilt. Just perspective.
I believe in hard work and slightly delusional self-belief. Not because confidence is worth performing, but because most worthwhile things look impossible before someone decides they aren't. I also think the UK wastes a lot of talent. Brilliant people end up on safe paths not from lack of ambition, but because the alternative feels uncertain. I understand that. I just don't think comfortable and meaningful are usually the same thing.
I like talking to people. If you're trying to figure out Oxbridge or land your first opportunity, reach out. If you're building something and want a second opinion, reach out. If you think I'm wrong about something, especially reach out. I'm more interested in the conversation than in being right.
If you're building something interesting, especially in healthcare, markets, or somewhere between the two, reach out. Email or LinkedIn, whichever you prefer.