Privacy-Focused AI Platform Hits 2M Users

Venice AI was founded by Erik Voorhees, a well-known figure in the cryptocurrency space and the founder of the crypto exchange ShapeShift. Voorhees has been a long-time advocate for decentralization, a principle he is now extending to artificial intelligence to counter the control of large tech companies. The platform is designed to be a private, uncensored, and open-source alternative for generative AI. Launched in May 2024, Venice AI's core feature is its privacy-focused architecture; it does not store user data on its servers, instead keeping interactions encrypted and localized to the user's browser. This approach is intended to prevent the kind of data surveillance and censorship that can be present on more centralized AI platforms. The platform has seen rapid user adoption, reaching its first million users in 13 months and hitting the 2 million user mark in just half that time. The platform's native token, VVV, is central to its ecosystem and operates on the Base network, an Ethereum Layer 2. The VVV token was launched in January 2025 with an initial supply of 100 million, 50% of which was allocated for an airdrop to early users and various AI and crypto communities. Staking VVV tokens grants users a proportional share of Venice's API capacity, allowing for ongoing use of the AI without per-request fees. Stakers also earn a yield, which has been noted to be around 18%. To create deflationary pressure on the token, Venice initiated a buy-and-burn program in November 2025, using a portion of its revenue to purchase and permanently remove VVV tokens from circulation. Venice provides access to a variety of open-source AI models for generating text, images, and code. The platform offers both a free tier with daily prompt limits and a Pro version for more advanced users. In addition to its web interface, Venice AI is also accessible through mobile apps. The project is part of a growing movement towards decentralized AI, which aims to distribute the control and operation of artificial intelligence across a network of participants rather than a single entity. This model is designed to enhance user privacy, increase transparency, and reduce reliance on a few large tech companies. Competitors in the privacy-focused and decentralized AI space include platforms like Okara and Krater.ai.