TrueNorth Secures $3M to Launch Finance-Specific AI Trading Platform, Opens Beta to 40,000 Users
December 4, 2025
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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Sources

Decrypt • Dec 4, 2025
TrueNorth Raises $3M to Build Domain-Specific AI for Finance
TradingView • Dec 4, 2025
TrueNorth Raises $3M to Build Domain-Specific AI for Finance
The Daily Hodl • Dec 4, 2025
TrueNorth Raises $3M to Build Domain-Specific AI for Finance