Vested's investment model gains an edge from proprietary data on employee sentiment and behavior. Signals like unsolicited negative comments, willingness to counter on price, or selling more shares than necessary provide unique insights into a company's health that traditional financial analysis lacks, forming a data moat.
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As platforms like AlphaSense automate the grunt work of research, the advantage is no longer in finding information. The new "alpha" for investors comes from asking better, more creative questions, identifying cross-industry trends, and being more adept at prompting the AI to uncover non-obvious connections.
The most valuable consumer insights are not in analytics dashboards, but in the raw, qualitative feedback within social media comments. Winning brands invest in teams whose sole job is to read and interpret this chatter, providing a competitive advantage that quantitative data alone cannot deliver.
WCM avoids generic AI use cases. Instead, they've built a "research partner" AI model specifically tuned to codify and diagnose their core concepts of "moat trajectory" and "culture." This allows them to amplify their unique edge by systematically flagging changes across a vast universe of data, rather than just automating simple tasks.
Acknowledging venture capital's power-law returns makes winner-picking nearly impossible. Vested's quantitative model doesn't try. Instead, it identifies the top quintile of all startups to create a high-potential "pond." The strategy is then to achieve broad diversification within this pre-qualified group, ensuring they capture the eventual outliers.
Instead of a generalist AI, LinkedIn built a suite of specialized internal agents for tasks like trust reviews, growth analysis, and user research. These agents are trained on LinkedIn's unique historical data and playbooks, providing critiques and insights impossible for external tools.
Vested works directly with employees because startups find small, one-off secondary transactions burdensome due to legal fees and cap table complexity. However, this dynamic inverts at scale. Once Vested facilitates millions in transactions for a single company's stock, the startup has a strong incentive to partner on a formal liquidity program.
Extreme conviction in prediction markets may not be just speculation. It could signal bets being placed by insiders with proprietary knowledge, such as developers working on AI models or administrators of the leaderboards themselves. This makes these markets a potential source of leaked alpha on who is truly ahead.
A sustainable competitive advantage is often rooted in a company's culture. When core values are directly aligned with what gives a company its market edge (e.g., Costco's employee focus driving superior retail service), the moat becomes incredibly difficult for competitors to replicate.
If a company and its competitor both ask a generic LLM for strategy, they'll get the same answer, erasing any edge. The only way to generate unique, defensible strategies is by building evolving models trained on a company's own private data.
Vested sources a differentiated data set by analyzing private company performance through state and local tax and labor filings. While the absolute numbers are often inaccurate for any given company, they are consistently inaccurate. Therefore, the trend line provides a reliable and valuable signal for a company's growth or decline.