Menlo Park-based Kleiner Perkins has raised $3.5 billion across two new funds, making one of the largest and most deliberate bets by a legacy venture firm on the current AI cycle.
The capital is split between a $1 billion early-stage fund and a $2.5 billion growth vehicle, giving the firm firepower across the full startup lifecycle.
The two funds
KP22, the firm’s twenty-second early-stage venture fund, totals $1 billion and will focus on backing founders at the earliest stages: teams building new AI products and platforms before they’ve reached scale. The fund continues Kleiner Perkins’ core identity as a company-builder.
In the meantime, KP Select IV is the firm’s new growth fund, raising $2.5 billion to support more mature companies that have already demonstrated strong market traction and are scaling rapidly.
At the growth stage, the firm says it will be more selective, focusing on companies that have reached clear inflexion points.
Where will they invest?
Kleiner Perkins has identified several sectors of focus across both funds, reflecting where they see AI driving the most durable transformation: professional services, healthcare, autonomy, cybersecurity, financial services, productivity tools, and industrial and physical-economy applications.
Its portfolio includes Google, Amazon, Figma, and Waymo, among many others. With the close of these two new funds, Kleiner Perkins continues to position itself as one of the most active and institutionally significant investors in the AI era.
The firm has framed its timing explicitly around what it calls an “AI super-cycle,” a period in which AI-native companies are reaching product-market fit and scaling faster than in any previous technology wave.
The $3.5 billion raise reflects a broader shift in venture capital strategy. Rather than focusing solely on seed or growth, Kleiner Perkins is explicitly building a portfolio architecture that can support companies from day one through IPO.
KP Select IV, in particular, signals that the firm wants meaningful ownership stakes in breakout AI companies before they go public.
