ModelMakr is an independent lab building AI for finance, designed by people who have done the job. Our tools take on the heavy lifting so professionals can decide faster and with more conviction, while people keep the final say.
Markets reward the investor who reaches a sound view first. AI can now read, compare and check information at a pace no team can match. ModelMakr puts that capability to work for the people making the decisions, with full transparency and their hands firmly on the controls.
Reading filings, building the numbers, drafting a view or preparing for an interview takes days. Our tools do the groundwork in a fraction of the time.
Every figure traces back to its source, every conclusion is challenged by a second reviewer, and the system says plainly how confident it is.
People set the mandate and the risk limits, and can overrule any decision at any time. Nothing changes silently, and every step leaves an audit trail.
Each one starts from a job we have done ourselves, from preparing for a banking interview to building an investment view and acting on it.
An AI interview coach for investment banking candidates. It runs realistic mock interviews on technical and behavioural questions, from M&A, DCF and LBO to Superday and HireVue practice.
An AI research platform that works the way a buy-side analyst does. It compares filings, earnings calls and reports against each other to find what changed and why it matters, then turns that into a trade view with an honest measure of confidence.
A systematic engine trading equities on event-driven and momentum strategies, using machine-learning signals and 1analyst's research as inputs.
What we learn about where AI helps investors most, where people still matter most, and how to combine the two.
Today's AI models read, compare and draft at a speed no team can match. Top professionals bring judgement, context and scepticism. This paper looks at what each does best, three structural weaknesses of current models, and how to design systems where the combination outperforms either alone.
Get it when it's published“Two decades of investing taught me what drives performance. ModelMakr is about delivering more of it, better.”
JP trained as a physicist and computer scientist, then spent more than twenty years investing.
He began in leveraged finance and M&A at Merrill Lynch and Barclays Capital and invested in European buyouts at Park Square Capital. He then moved to the hedge funds GLG, Millennium and ExodusPoint, before running his own credit book at Palm Lane Capital. Throughout, he built his own quantitative screening tools, later adding machine learning and language models.
Since 2025 he has worked full-time on AI for finance, including building the benchmarks used to train and test frontier AI models on financial analysis.
Occasional updates on releases, early access and research. No noise.