The Problem: Generic AI's Failure in High-Stakes Finance
A significant gap exists between the promise of Artificial Intelligence and its actual performance in financial markets, leading to billions in misallocated capital. Currently, 54% of investors report using tools like ChatGPT for trading and investment decisions, yet only 11% express trust in the results. TrueNorth has secured $3 million in pre-seed funding to develop specialized AI that bridges this critical gap.
The funding round was led by CyberFund and included participation from Delphi Labs, SNZ, GSR, and Ocular. This capital will be used to build what the TrueNorth team describes as "the reasoning layer for financial intelligence"—domain-specific AI designed to avoid the hallucinations and inaccuracies that plague general AI models when financial stakes are high.
"Every vertical should have a specialized AI," states Willy Chuang, co-founder at TrueNorth. “Legal has Harvey. Healthcare has OpenEvidence. But finance, the highest-stakes domain, is still using models trained on Reddit threads and the open web. We're fixing that."
The Generic AI Problem: Fast Markets, Slow Models
The TrueNorth team, drawing on experience from backgrounds at Meta, Temasek, and Goldman Sachs, has identified firsthand how generic AI models struggle in financial environments. These models tend to hallucinate, fail to grasp crucial market context, and lack the sophisticated reasoning that professional traders employ to navigate market volatility.
“Generalized AI falls apart in financial environments,” explains Willy Chuang, co-founder at TrueNorth. “Markets move too fast, the context is too deep, and mistakes are too costly. Domain-specific financial intelligence isn’t optional; it’s the future. And we’re the first to deliver it."
This realization has been central to TrueNorth's core strategy: developing financial AI that is specialized, operates in real-time, and is grounded in expert reasoning. The platform achieves this by converting elite trader expertise into AI agents. This process involves structured playbooks, real-time data fusion, and proprietary models meticulously trained on financial market logic.
Initial performance benchmarks are highly encouraging. Internal testing indicates a 98% accuracy rate on finance-specific tasks, representing a 28% improvement over leading general AI models. Furthermore, latency has been reduced by 80%. Early beta users have demonstrated a 30-day retention rate of 33%, which is approximately double the industry average.
Expert Traders as Digital Twins
Professional traders dedicate significant time each day to scanning markets, validating price levels, managing risk, and meticulously journaling their decisions—tasks that are traditionally difficult to automate without specialized engineering skills. Retail traders, on the other hand, often face the challenge of lacking the necessary pattern recognition and strategic frameworks to trade consistently, even with available tools.
TrueNorth addresses both these challenges by transforming expert trading workflows into AI-powered digital twins. Through the use of structured playbooks and agentic workflows, top traders can now encode their strategies using natural language. Simultaneously, everyday traders can benefit from acting with the logic and discipline of the experts they follow. The startup has already established partnerships with leading financial educators who collectively represent over 1.5 million followers.
“Our platform is the first to model how professionals actually reason through markets. It abstracts complexity while preserving discipline,” said Alex Lee, co-founder at TrueNorth. “Having agents identify trade setups and highlight risks in real-time, users can act with the logic of professionals without needing their decades of pattern recognition and institutional knowledge.”
Public Beta Launch with High Demand
With substantial backing from CyberFund, Delphi Labs, SNZ, GSR, and Ocular, along with strategic investments from prominent figures such as Bryan Pellegrino (LayerZero), WeeKee (Virtuals Protocol), and Jordi Alexander (Selini Capital), TrueNorth is launching its public beta. The platform is entering the market with a waitlist of over 40,000 users eager for advanced financial intelligence.
"AI is transforming the way people interact with apps," commented Konstantin Lomashuk, co-founder at Cyberfund. "Truenorth will redefine how people trade. With Truenorth people will trade better with AI-powered insights."
The company is actively collaborating with early adopters to co-develop the agentic workflows that are expected to define the future of AI-native investing. These workflows aim to enable AI models to not only answer questions but also to execute strategies, manage risk effectively, and adapt to real-time market regime changes.
The public beta is scheduled to open today.
About TrueNorth
TrueNorth specializes in building domain-specific AI infrastructure for the finance industry. The platform translates the expertise of professional traders into adaptive intelligence that everyday investors can utilize. By integrating structured reasoning, real-time data feeds, and proprietary models, TrueNorth delivers financial insights that are characterized by accuracy, contextual awareness, and readiness for execution.