Sahara AI packages data, models, and agents on-chain, bringing the 'AI asset layer' from PPT to the chain; the execution logic of Royalty Vault's automatic profit distribution allows contributors to earn revenue like receiving royalties, which is a rare original design among many current AI × Web3 projects.

The BUIDLPAD public offering window is from June 8-18, with a hard cap of 8.5 million USD, selling only 1.4167% of circulation, corresponding to an FDV of approximately 600 million; 100% TGE unlock, with individual quotas of 50-3000 USD. For secondary investors, this 'small cap + full circulation' means concentrated liquidity pressure on the first day but also leaves room for early participants to profit. Just look at the trend of $Layer to understand.

The financing side has absorbed 43 million USD, with a lineup from Polychain to Pantera, Samsung Next, lined up, and executives from Midjourney and Anthropic on the advisory board, showcasing at least a network of industry resources; what really needs to be seen is when the on-chain transaction data will expand. SIWA's public testing has 3.2 million accounts and 1.4 million DAU, where users can earn test coins by playing tasks with Faucet; the faucet traffic of Bitget Wallet has verified its cold start appeal. Data annotators have exceeded 200,000, indicating that the story of 'contribution equals revenue' has buyers, but to monetize, we still have to wait for the mainnet to be solidly implemented.

Horizontal comparison: FET circulating market value is 1.96 billion, TAO 3.4 billion, RNDR 2.03 billion, ARKM 0.123 billion; Sahara's online FDV is 600 million, positioned between Arkham and Render. There is a value creation space of 3-4 times to catch up with FET. It is categorized under the 'AI asset infrastructure' pocket. 600 million FDV is not cheap, but not outrageous yet; if Royalty Vault can achieve tens of thousands of daily active paid users, each percentage point increase in market share could theoretically expand the valuation by over 1 billion. First, participate in BUIDLPAD, then adjust positions based on mainnet data; true large positions will need to wait for the mainnet's six-month retention rate and GMV proof.

Key observation points: ① Whether the mainnet goes live as scheduled in Q3; ② Whether royalty settlement is frictionless; ③ The number of institutional nodes and their yield; ④ Whether the transaction volume of datasets and models can form an exponential climb.

Sahara brings the ownership economics of Web3 into the AI supply chain, with the right direction, sufficient funding, and validated traffic; all that remains is execution power.