“We were living under the tyranny of keywords - you only find what you already know to look for. LinqAlpha helped us break that pattern.”

— Kate (Minji) Kim, Portfolio Manager, MUST Asset Management

About MUST Asset Management

Founded in 2006, MUST Asset Management is one of Korea’s longest-standing long-only equity firms, known for its disciplined, bottom-up investment philosphy and collaborative research culture.

The firm’s Korea-focused equity portfolio has consistently delivered over 22% annualized gross returns since its first fund launch in 2009. The team maintains a strong focus on consumer-facing (B2C) holdings and has long been recognized as an early adopter of innovative technology. Operating under its distinctive “N-divided-by-1” decision model, seven portfolio managers share equal accountability for every investment — a structure that enforces analytical rigor and collective conviction.

The Challenge: The Tyranny of Keywords

By 2024, MUST’s analysts were tracking a rapidly expanding universe of information - from earnings transcripts to consumer sentiment and online discourse.

But as data multiplied, clarity diminished. Traditional search tools forced analysts to rely on keywords, limiting discovery to what they already knew to ask. The result was what Kim describes as the “tyranny of keywords” - a research process that was rich in data but poor in signal.

“We knew we had all the information,” recalls Kim. “What we lacked was a way to see how sentiment was shifting - to connect the dots across time, not just capture snapshots.”

The team needed a way to observe narrative changes dynamically, uncover early indicators of sentiment shifts, and keep pace with market developments without being buried in backward-looking reports.

This question sparked LinqAlpha’s first version of a social media monitoring system, designed to help investors read market psychology by observing time-series developments in social media post volume - the foundation for what later became LinqAlpha’s Social Media Analysis Agent.

Co-Designing the Social Media Analysis Agent

This collaboration marked one of LinqAlpha’s early design partnerships, where LinqAlpha engineers and MUST’s investment team worked side-by-side to translate real research workflows into product capability. The result was the Social Media Analysis Agent - an AI agent that transforms unstructured online conversations into structured, time-series insight.

The goal was clear: to help analysts detect and visualize market sentiment shifts before they appear in headlines by transforming unstructured online activity into structured, interpretable insight.

• The Agent enables analysts to visualize how narratives evolve across time, tracking sentiment and attention flows across public social channels.

• For consumer and internet sectors, it surfaces early indicators of changing tone or emerging themes, which analysts can overlay with stock performance to identify inflection points sooner.

• Its intuitive time-series chart replaces manual search with proactive discovery — showing when interest is accelerating or fading in real time.

In parallel, Earnings Manager complements this workflow by automatically delivering earnings summaries, First Takes, and direct links to calls, ensuring analysts stay informed without manual effort. Together, these Agents exemplify how LinqAlpha builds in partnership with the industry - solving the problems investors face daily through practical, co-designed solutions.

“It’s about spotting what’s changing sooner - and having those signals surface automatically, not after the fact.”

Impact: Building the Future of Research

With LinqAlpha’s Social Media Analysis Agent, MUST’s analysts can now see evolving narratives across time for the companies they follow, while Earnings Manager keeps them continuously informed through real-time updates and structured takeaways. What once required hours of searching and reading now happens in minutes.

For LinqAlpha, this collaboration reflects the foundation of its design partnership model: building research tools directly with the analysts who use them. By turning social sentiment and earnings data into time-series signals and integrating them seamlessly into daily workflows, LinqAlpha helps research teams move faster without losing depth or context.

Each product milestone begins with a real problem from the field - and ends with a practical system that gives investors clearer visibility, faster reactions, and more confidence in their judgment.