The retail investor in 2026 has more information than any pension manager had in 1990, and worse outcomes. The problem isn't access. It's depth. Reading one 10-K properly takes an evening, and most people own twenty stocks. So research gets skipped, and conviction gets borrowed from headlines and hot takes instead of evidence.
We thought: if reasoning models can write a research memo as well as a junior analyst, every investor should have one. Not to pick the next moonshot, but to do the unglamorous work: read the filings, run the same 167 checks on every company, cite every claim, and lay out the bear case next to the bull case. You make the call. That's the entire product.
Builds the AI research engine that powers Claremont. Computer Science at Harvey Mudd College, with a focus on applied AI and large reasoning models. Multiple early-stage startups under his belt before this: the kind of operator who has shipped a v1 at 3am and learned every lesson the hard way.
Pomona College, Class of 2026. After a stint at a Korean hedge fund, went on to run his own discretionary book and personally posted a +265% cumulative return over four years. His investment process (business quality, valuation discipline, conviction frameworks) is what the 167-point research framework encodes. The patient half of the partnership.