The Middle Finger Research Institute releases large models of AI property service scenarios and the first product "AI Bidding Agent".

On April 18th, the "2025 China Property Services Top 100 Enterprises Research Results Release Conference and the 18th China Property Services Top 100 Entrepreneurs Forum" was held in Xiong'an. At the conference, the China Index Research Institute, in collaboration with Xiaobing Technology and Zhi Jian Technology, officially released the "AI Property Service Scenario Large Model" and the first landing product "AI Bidding Agent", marking a new stage in the digital transformation of the property management industry with AI deep empowerment. Huang Yu, Executive Vice President of the China Index Research Institute and Director of the China Real Estate TOP10 Research Office, said, AI Bidding Agent focuses on property bidding scenarios and, through local deployment, can automatically complete tender writing in 3 minutes, increase bidding participation by 5 times, reduce bid failure rate by 100%, and increase the bidding success rate by 300% while ensuring the security of enterprise data. In the future, the China Index Research Institute plans to launch more useful and practical AI service products according to market development and customer needs to empower industry development. The CEO of Xiaobing Technology stated that the property service industry is accelerating towards a stage of refined and professional competition, and the traditional manual bidding mode is no longer able to meet the high-frequency and fast-paced market demands. Based on the massive industry data accumulation and AI deep learning technology of the China Index Research Institute, AI Bidding Agent innovatively developed a vertical large model in the property service field, coupling AI with industry experience to build an intelligent decision-making system covering the entire bidding cycle for enterprises, promoting bidding processes towards digitalization. Taking bid opportunity insights as an example, in the traditional bidding process, a lot of effort is spent on pre-screening but it is difficult to accurately assess the probability of winning the bid. With the AI Property Service Scenario Large Model, companies can match their qualifications and bidding requirements, target high-value projects with over 85% match rate, and filter out inefficient bid information, resulting in a 5-fold increase in bid participation. With AI's multi-dimensional evaluation capabilities, in addition to predicting bidding success rates, the AI Property Service Scenario Large Model's built-in peer intelligence database can help companies understand peer's pricing strategies, market size, operating costs, etc., to establish differentiated competitive advantages. Furthermore, during the bid writing stage, the AI Property Service Scenario Large Model achieves automatic content filling in seconds, compressing the bid preparation cycle by 90%. Additionally, from the perspective of evaluators, the model scans for deficiencies in the bid document, increases coverage of score points by 97%, effectively controls bid failure risks, and increases bidding success rate by 3 times.