RoboStrategy Raises $33.9 Million Through Private Share Issuances

By Amit Chowdhry • Today at 1:02 PM

RoboStrategy announced that it has completed a series of private share issuances to institutional investors. The transactions were completed between June 26 and June 29, 2026.

RoboStrategy issued an aggregate of 1,346,668 shares of common stock at a weighted average price of $25.17 per share.

The private placements generated gross proceeds of approximately $33.9 million before deducting offering expenses.

RoboStrategy is a registered closed-end fund that provides exposure to private companies in robotics and physical AI.

The fund intends to use the net proceeds to support follow-on investments and other capital deployments within its portfolio of private, venture-backed robotics and physical AI companies.

RoboStrategy said the planned investments will focus on transactions expected to be accretive to the fund and its shareholders.

The shares were issued in private placement transactions exempt from registration under the Securities Act of 1933 under Section 4(a)(2) and Regulation D.

The shares have not been registered under the Securities Act and may not be offered or resold unless they are registered or qualify for an exemption from registration requirements.

RoboStrategy intends to file a registration statement covering the resale of the shares under the terms of the applicable registration rights agreements.

Titan Partners, a division of American Capital Partners, acted as the sole placement agent for the offering.

RoboStrategy is a closed-end management investment company focused on public-market access to private robotics and physical AI innovation.

The fund focuses on high-conviction equity positions in robotics and physical AI companies, including companies such as Figure AI, Apptronik, Dyna Robotics, Dexmate, and other developers of autonomous systems and related supply chain technologies.

RoboStrategy was created to connect public markets with private innovation in technologies that are changing labor, productivity, and the relationship between humans and intelligent machines.