The purpose of civil and commercial jurisprudence observation is to realize the intelligent and innovative development of social governance and to improve the efficiency of related cases. This paper develops a civil and commercial jurisprudence case information analysis system that utilizes MVC architecture and intelligent technology. The BERT pre-training model and self-training model are combined for the construction of a civil and commercial jurisprudence legal information extraction model, which helps judicial personnel understand the scope of civil and commercial jurisprudence cases in the process of social governance. Then, the ILJP is used as the basis to combine the fact encoder, the element predictor and the legal cause predictor to carry out the construction of the interpretable legal cause intelligent research and judgment model, which provides an intelligent research and judgment program for the civil and commercial jurisprudence social governance cases. The effectiveness of the civil and commercial law case analysis system is an important guarantee to enhance intelligent social governance, so this paper carries out a test and analysis of its intelligent algorithm and system performance. The results show that the legal information extraction model tends to stabilize after the first 15 iterations of training, and its validation loss value is around 0.173, and the training loss value of the model is around 0.008 when the training of the intelligent research and judgment model reaches 200 rounds. When the information analysis system of civil and commercial law cases reaches 1,000 concurrent users, the average response time of each logical operation does not exceed 3s, and the occupancy rate of CPU and memory resources is over 30%. The information age needs to fully combine technology and social governance in order to deeply mine the information of civil and commercial jurisprudence related cases, improve the efficiency of social governance, and innovate the intelligent development of social governance.