Beijing Caizhi Technology

Beijing Caizhi Technology Co., Ltd. operates at the intersection of knowledge engineering and artificial intelligence, positioning itself as a developer of trustworthy Artificial General Intelligence (AGI). The company was established in 2016 to address a critical vulnerability in the AI sector: the unreliability and potential for 'hallucination' in standard large language models, which impedes their use in mission-critical and low-tolerance professional environments.

The firm's leadership, including founder and CEO Dr. Xu Jianjun and chief researcher Li Qi, originates from the prestigious Knowledge Engineering Laboratory (KEG) at Tsinghua University. This academic background is central to the company's methodology. Drawing on 25 years of research direction from KEG, the team focuses on creating AI applications that are both explainable and traceable. This journey culminated in a significant milestone in 2021 when the company, in partnership with the Beijing Institute of Artificial Intelligence, undertook a major project for the Ministry of Science and Technology's "New Generation Artificial Intelligence in 2030" initiative.

The core of Caizhi Technology's offering is its proprietary "Shenzhi Intelligence" knowledge model. Developed over four years, this system integrates vast amounts of verified knowledge from normative documents across multiple industries into its framework. By embedding ontological cognitive graphs with this structured data, the model works in conjunction with foundational large models, such as the Zhipu GLM series, to deliver accurate and verifiable results. This approach provides a ready-to-use, trusted intelligent knowledge service that enables the rapid and standardized deployment of large-scale AI applications. The business model appears to be enterprise-focused, providing solutions and standardized products directly to large government and corporate clients. The company has secured contracts with prominent institutions like the General Office of the State Council and Beijing Enterprises Group, achieving profitability.

Keywords: trustworthy AGI, explainable AI, traceable AI, knowledge engineering, large language models, enterprise AI solutions, government AI, Zhipu Ecological Fund, Tsinghua University KEG, Shenzhi Intelligence model, ontological cognitive graphs, AI for enterprises, normative data AI, interpretable AI, AI model implementation, knowledge-based AI, Beijing AI, Dr. Xu Jianjun, large-scale model applications, trusted knowledge services