Vested is a venture secondaries platform providing liquidity to startup employees, targeting the often-ignored market of rank-and-file employees who abandon stock options due to the high cost of exercising them.
The firm utilizes a proprietary, machine learning-based model to select and price shares, aiming to build diversified portfolios of the top 20% of venture-backed companies.
Vested's model uses alternative data signals, such as key employee departures and hires, to predict startup success and proactively sources deals by contacting employees of target companies.
The long-term vision is to leverage its unique data set to help create a more efficient, transparent, and eventually indexable secondary market for private assets.
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Concerns Raised
The eventual arrival of well-funded asset managers as direct competitors.
The slow feedback loop for validating models due to the illiquidity and long time horizons of private markets.
Opportunities Identified
The massive, $200-300 billion addressable market of abandoned employee stock options.
Leveraging proprietary data to become a key player in the emerging field of private market indexing.
Scaling by partnering with startups to provide a "liquidity program in a box" for their employees.