Grayscale introduces decentralized AI token funds for TAO and SUI

Source Fxstreet
  • Grayscale announced the launch of two new crypto investment funds for TAO and SUI tokens.
  • Grayscale Bittensor Trust and Grayscale Sui Trust will focus solely on providing price exposure to TAO and SUI tokens.
  • TAO and SUI could experience rallies following the launch of the new Trust funds.

Grayscale announced on Wednesday the establishment of two new crypto Trust funds for Bittensor (TAO) and Sui (SUI) tokens. The move adds to the firm's growing list of decentralized AI funds.

Grayscale launches Bittensor Trust and Sui Trust Funds

Crypto asset manager Grayscale introduced two new crypto investment funds for decentralized AI token TAO and Layer-1 token SUI, namely the Grayscale Bittensor Trust and the Grayscale Sui Trust. 

The new funds are single-asset funds tailored solely to provide investors with exposure to the potential price growth from the development of Bittensor and Sui protocols. The firm also indicated that the products are now available for daily subscription to eligible investors, whether as individuals or institutions.

The launch of these crypto funds signifies Grayscale's ongoing efforts to expand its decentralized investment offerings as it continues to provide investors with crypto exposure.

"With the launch of Grayscale Bittensor Trust and Grayscale Sui Trust, we continue to provide investors with familiar products that enable access to tokens at the cutting edge of the crypto ecosystem's continued evolution," said Grayscale's Head of Product & Research, Rayhaneh Sharif-Askary. 

The launch of the new investment products could significantly impact the prices of TAO and SUI tokens. Following the announcement, SUI is up 3.3%, while TAO is down 3.1%, stretching its weekly loss to 18%.

Grayscale had previously launched Trust funds for other AI-based crypto tokens, including NEAR, RNDR and FIL, allowing investors to gain exposure to their price performance.

Disclaimer: For information purposes only. Past performance is not indicative of future results.
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