AI Startups Building for Hedge Funds (alexizydorczyk.com)

A curated, continuously updated page has been launched to track startups using large language models (LLMs) as a core part of their product offering to alternative asset managers (hedge funds, private equity, VC, etc.). The list was moved from the author’s Magis blog to a standalone page for easier maintenance and referencing, with plans to later split entries by public vs. private market focus and other categories. The compiler excludes established firms that have merely added an AI product and flags founders with hedge fund practitioner experience (📈) or Silicon Valley AI/ML backgrounds (💻) to signal likely product-market fit and technical pedigree. Web-extraction and general financial-data providers are cataloged separately. For the AI/ML community, the page is a practical map of where LLM-driven innovation is being deployed in investment workflows—research synthesis, automated due diligence, idea generation, and desk-level assistance—highlighting startups that bake LLMs into their core stack rather than bolt them on. Important implications include vendor discovery for quant and ML teams, signals about modality (NLP-first solutions), and considerations around data quality, model hallucination, latency, security and regulatory/compliance risks when LLMs ingest proprietary or market-sensitive information. The list invites contributions and corrections, aiming to improve visibility and due diligence for practitioners evaluating AI vendors in finance.