How Balyasny Asset Management built an AI research engine

Balyasny Asset Management⁠⁠(opens in a new window) (Balyasny) is a global, multi-strategy investment firm with approximately 180 investment teams across diverse asset classes and geographies. The firm operates in a highly competitive and dynamic industry where conviction, precision, and speed are all critical to success. Facing an increasingly complex market environment with surging volumes of financial data, Balyasny saw an opportunity to reimagine the investment research process using AI.

In late 2022, Balyasny established an Applied AI team: a centralized group of 20 researchers, engineers, and domain experts tasked with building AI-native tools that embed directly into team-level workflows. Their flagship product, an AI investment research system, is designed to reason, retrieve, and act like a skilled analyst.

“AI is enabling our teams to apply first principles thinking faster, across more data, and with more structure.”

—Charlie Flanagan, Chief AI Officer

Addressing limitations of legacy research workflows

Investment research is complex, high-stakes, and time-sensitive. Analysts must parse through thousands of documents, from market data and research to regulatory filings. Human expertise remains essential, but traditional methods are time-consuming and difficult to scale.

Off-the-shelf AI tools often can’t handle structured and unstructured data together, lack workflow orchestration, and aren’t built to meet institutional compliance standards. Balyasny needed something purpose-built: an AI system that could think like an analyst, move at the speed of a machine, and work within strict compliance boundaries.

Four lessons from Balyasny’s approach to AI at scale

1. Evaluate models before deploying them

“We evaluate models the way we evaluate investments: on fundamentals. GPT-5.4 proved it could plan, reason, and execute with real rigor.”

—Su Wang, Senior Research Scientist

2. Foster deep collaboration between users and AI partners

—Jonathan Park, Product Manager