A ledger of non-consensus bets — from early crypto and cross-border fintech to building in AI today.
I grew up between three countries and as many healthcare systems, none of which agreed with each other. Then I did the thing everyone recommends and bought the wearables — and ended up with five dashboards, four scores, and no read on what any of them actually wanted from me. A bad number could quietly cost me a morning. That's the problem I build against.
Oriya normalizes Oura, Garmin, Whoop, and Apple onto one fair 0–100 recovery index and hands a squad a single number to compete on — how well you recovered, not whose device runs generous. Private beta in SF & NYC; the long arc is health data you own.
“Diana can move from thesis to implementation faster than anyone I've seen. She identified our growth lever in the first week, then built the system to exploit it.”
“Working with Diana feels like having a chief operating officer who also speaks fluent Solidity. She understands the technical architecture and the market architecture simultaneously.”
“She's built in more markets than most founders visit. That pattern recognition about what actually works cross-culturally — I haven't found it anywhere else.”
I spent years building the hard version of fintech and web3 — products where the deep-tech problem and the interface were the same problem. I'm bringing that judgment, and the product-and-UX edge that came with it, to a small number of AI startups now: the growth loop that hasn't clicked, the inference bill outrunning the product, the stack one decision from working. If you're teaching yourself into tech, that conversation's free — those I answer first.
my inbox is open ↗