In the field of synthetic biology, data is the new "oil." We have constructed a powerful data-driven management system, at its core an intelligent decision-making and knowledge management platform that integrates big data, artificial intelligence, and machine learning technologies. This platform is capable of real-time collection, integration, and analysis of vast amounts of data derived from high-throughput experiments, bioinformatics analyses, literature databases, and market feedback. Through advanced AI algorithms, we can accelerate critical stages such as gene circuit design, strain optimization, and enzyme engineering, predict experimental results, and optimize experimental protocols, thereby significantly shortening the R&D cycle and boosting success rates. Furthermore, the platform serves as the repository for the company's core intellectual property and technical know-how. Through structured knowledge bases, intelligent search, and visualization tools, it facilitates the efficient accumulation, sharing, and transfer of internal knowledge, preventing redundant work and promoting the reuse of innovative experiences. This data-driven intelligent management model ensures that our decisions are based on the most accurate and comprehensive information, thereby maintaining a leading position in fierce market competition.
To ensure that the production process is in a controllable state as well as to guarantee the quality of production process, BSAZ conducts analysis, diagnosis and monitoring to all the techniques adopted in production process, analyzing process and services which may directly or indirectly influence product quality. What’s more, BSAZ takes key control of product characteristics that are not easy to analyze, particular skills required for equipment maintenance and operation and particular processes. Deficiencies are dealt with timely and process parameters are monitored, controlled and verified on a reasonable frequency in production process so as to ensure that all equipments, operators and other conditions meet the requirements of product quality.
