TrueNorth Secures $3M to Launch Finance-Specific AI Trading Platform, Opens Beta to 40,000 Users

December 4, 2025
TrueNorth Secures $3M to Launch Finance-Specific AI Trading Platform, Opens Beta to 40,000 Users
  • The platform aims to deliver a real-time financial intelligence system that reduces hallucinations and enhances decision-making in fast-moving markets.

  • Traders can encode strategies and workflows in natural language, enabling users to operate with professional-level logic without decades of pattern-recognition experience.

  • Chainwire is the press release distribution platform for the funding news, dated December 4, 2025.

  • The announcement emphasizes building specialized AI to improve finance-related tasks such as data analysis, risk assessment, and decision support.

  • Early benchmarks claim 98% accuracy on finance-specific tasks, about 28% better than leading general models, plus an 80% reduction in latency, with 30-day retention around one-third of beta users.

  • Internal testing indicates high task accuracy and lower latency, with beta users reporting strong reliability for traders seeking consistent reasoning tools.

  • A promotional disclaimer notes sponsorship by The Daily Hodl and urges due diligence for high-risk investments.

  • Public beta opens today with an invite code and the company aims to develop AI-native investing where models execute strategies, manage risk, and adapt to regime changes in real time.

  • Founders emphasize finance as a high-stakes domain requiring specialized AI grounded in market logic, not generic models.

  • TrueNorth seeks to replace broad, hallucinatory models with specialized, reasoning-based AI tailored to financial contexts.

  • Founders bring experience from Meta, Temasek, and Goldman Sachs, highlighting concerns about general AI misinterpreting market contexts under pressure.

  • The funding aims to build AI systems optimized for financial services with industry-specific workflows.

  • TrueNorth is building AI agents that mirror elite trader expertise through structured playbooks, real-time data fusion, and market-logic trained models, creating digital twins of top traders for both professional and retail users.

  • The funding round totals $3 million, with no additional terms, investors, or timelines disclosed in the provided information.

  • TrueNorth has educator partnerships reaching over 1.5 million followers and a waitlist exceeding 40,000 for the public beta launching immediately.

  • The report is presented in a press-release style aimed at business and tech audiences, outlining a funding milestone and strategic objectives.

  • A disclaimer notes the article reflects the author’s opinion and is not investment advice.

  • Founders Willy Chuang and Alex Lee lead the venture, with backers including Bryan Pellegrino, WeeKee, Jordi Alexander, and other investors from CyberFund, Delphi Labs, SNZ, GSR, and Ocular.

  • The funding seeks to accelerate the development of a reasoning layer for financial intelligence.

  • Public beta opens to more than 40,000 waitlisted users, with investors including Pellegrino, WeeKee, and Alexander supporting the launch.

  • Public beta launches today for over 40,000 waitlisted users; sign-ups are available at the company site with an invite code.

  • The piece frames the risk of generic AI in fast markets and positions TrueNorth as the first to deliver finance-specific intelligence grounded in expert reasoning.

  • Key supporters include strategic angels and institutional backers with a combined reach of more than 1.5 million followers.

  • The platform’s AI-native trading workflows will support data interpretation, strategy management, risk assessment, and adaptation to evolving markets.

  • Early beta users show a 30-day retention rate of about 33%, roughly double the industry average.

  • TrueNorth’s $3 million pre-seed round was led by CyberFund, with participation from Delphi Labs, SNZ, GSR, Ocular and several angels, to develop a domain-specific AI for finance.

Summary based on 8 sources


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