XUNCE Technology (03317) May ARR revenue increased by 320% compared to the previous month. TokenOS received endorsement from a national level exchange.

On the evening of June 29th, XUNCE Technology (03317) signed a strategic cooperation agreement with the Beijing International Big Data Exchange. The two parties will collaborate in four major areas: tokenization of vertical data, intelligent data circulation, digital asset services, and standardization of databases in the biopharmaceutical industry. This follows XUNCE's partnership with the Shenzhen Data Exchange in April, marking a strategic presence in national-level data platforms and forming a comprehensive strategic loop. This cooperation signifies the transition of XUNCE's data tokenization strategy from conceptual validation to large-scale implementation. In May, XUNCE launched the world's first TokenOS, enabling real-time conversion of diverse and heterogeneous data into tokenized scenarios that are measurable and quantifiable. Token calls in May increased by 320% compared to the previous month, with token revenue reaching over 5% of total revenue. The company aims to increase this to 20-30% by the end of the year, transitioning from project-based billing to token consumption billing. In parallel with industry depth expansion, XUNCE has partnered with PATEO and SAIMO to enter the physical AI and world model fields. Collaboration with Turing Quantum advances the "Quantum + Token Factory" concept. XUNCE has also signed agreements with three major domestic GPU manufacturers - Mu Xi, ILUVATAR COREX, and BIREN TECH - becoming a data infrastructure service provider covering three major computational systems. Analysts at Huatai point out that XUNCE's scenario token pricing ranges from $10 to $100 per million tokens, exceeding the value of general large model tokens by ten times. This premium is attributed to proprietary data, millisecond response times, and industry expertise. Concerns about the impact of price reductions on large models in the market are actually misconceptions - as the cost of underlying models decreases, it lowers the barrier for AI deployment, enhances ROI, and drives continued growth in private data investment and token calls.