AlphaRaise Limited is registered in Hong Kong. The company is small, founder-led, and early, and we'd rather say that plainly than let a visitor guess.
The team's experience spans institutional research, private capital advisory and secondaries diligence across a large number of GPs, and live IR and fundraising execution for an active fund. That includes building LP pipeline frameworks, managing roadshows, and running capital-formation infrastructure. This is why AlphaRaise reflects how the job actually works day to day, not an outside guess at the market.
A backtest run on real LP interaction data, a live LP dataset, not a survey, found that named-person warm introductions did not outperform cold outreach in aggregate. It also found a clear fatigue signal. Introduction success rates fell from roughly 36% on a first ask to 16% by the fourth from the same intermediary, and the highest-volume intermediaries showed the lowest engagement. That finding directly shaped how AlphaRaise's allocation engine recommends who to ask, and how often.
AlphaRaise is currently in active development and private beta. Nothing is publicly live yet. Three provisional patent applications have been filed, covering cross-source investor entity reconciliation, fatigue-aware introduction-path optimization, and a re-commitment survival-hazard model. The algorithms are a genuine asset. The durable advantage is the proprietary, outcome-verified data they run on.