Thought Leadership in Practice: Engineering the Next-Gen AI Framework with Arrowpoint Investment Partners
At LinqAlpha, we have always believed that applying AI to high-stakes finance requires more than just cutting-edge models, it demands a rigorous, systems-based approach.
Today, we are sharing insights from our ongoing strategic alignment with Arrowpoint Investment Partners (“Arrowpoint”), one of Asia’s most forward-thinking multi-strategy hedge funds, backed at launch by prominent institutional investors including Blackstone, the Canada Pension Plan Investment Board (CPPIB), and Temasek’s Seviora Capital. Arrowpoint began trading in 2023 with over $1 billion in assets under management and has quickly established itself as a deep, disciplined platform with a multi-pod, multi-strategy approach spanning equities, macro, fixed income, and alternative strategies.
A Meeting of Minds: Defining the Framework
The gap between academic AI research and the operational realities of the investment platform is vast. Bridging it requires a dialogue between deep research capabilities and practical, battle-hardened engineering.
Over the past year, our team has worked closely with Joo Lee, Co-Founder and CTO of Arrowpoint. A veteran technologist with over 15 years of experience building trading and risk systems at institutions like Goldman Sachs and Endowus, Joo brings a pragmatism to AI that is rare in the hype cycle.
This alignment was on display at ICLR '25 and CIKM '25, where LinqAlpha Co-founder / Co-CEO Jacob Chanyeol Choi and Joo Lee co-presented on the future of “Compound AI Systems.”
As Joo Lee explained during the session:
"The goal is to build modular, scalable systems so that when better models come, you can just plug them in. You are betting on the collective progress of the entire AI industry. Ride the wave, don’t build the wave."
Beyond the Black Box: A Joint Thesis
Through our ongoing dialogue and joint panel sessions, we have crystallized a playbook for how multi-strategy funds should approach AI adoption. The consensus is clear: Single-agent LLMs are insufficient for institutional finance.
Our shared conviction in Compound AI Systems led to this collaboration, which focuses on developing the Leadership Intelligence layer—the systems that must be built to differentiate. As Joo noted during our ICLR session, investment research requires deep skepticism. A standard LLM is often too "agreeable" for a Portfolio Manager looking for idiosyncratic risks.
Our Framework’s Five Architectural Pillars:
Multi-Agent Architectures: Moving beyond monolithic prompts to systems where agents critique and validate one another, mirroring the analyst-PM relationship.
Skepticism by Design: Engineering systems that prioritize factual density and counter-arguments over fluency, addressing the risk of Confirmation Bias Reinforcement.
Modular Infrastructure (The Plumbing): Prompt engineering and model tuning typically account for under 30% of total effort; most work lies in the "plumbing". We focus on the critical orchestration layer, building a model gateway so the base model is a swappable part.
Production Hardening: Moving from "cool demo" to reliable, day-one value on the Investment System, by managing complexity, scalability, and resilience.
Bias Mitigation: Developing governance layers and using an evaluation harness with a golden set of questions to ensure the AI reflects market data, not the biases inherent in the training set.
Research Collaboration Founded on Design Partnership
What sets this strategic alignment apart is the depth of research collaboration, embodying the spirit of a design partnership.
By working with Arrowpoint to benchmark how different models handle financial context, we are tackling the “black box” problem that prevents many funds from fully adopting generative AI.
This work reflects a shared commitment to transparency, rigorous evaluation, and production-grade AI systems that can be trusted in high-stakes decision making.
Looking Ahead
Arrowpoint Investment Partners represents a new breed of hedge fund: tech-forward, scalable, institutionally anchored, and built on a foundation of rigorous engineering.
We are excited by the progress of our current collaboration and the fact that Arrowpoint recognized that our compound AI architecture and research-first DNA are uniquely suited to address their requirements.
As we move forward, we remain committed to the philosophy we shared on stage in Singapore: Great AI in finance isn't magic. It's engineering.