In the context of Work Integrated Learning (WIL), student feedback is extremely crucial. It offers a unique perspective on the efficacy of the learning journey, the applicability of the course content, and the influence of practical experiences on their academic comprehension. Feedback from students allows educators and institutions to pinpoint the strong and weak areas of the WIL program, thereby facilitating necessary modifications for enhancements. It also encourages a dialog, creating an atmosphere of mutual understanding and collective accountability for learning. Furthermore, it gives students an active role in their education, promoting engagement and enriching their learning journey. Hence, student feedback is not just beneficial, but essential for the ongoing refinement and effectiveness of Work Integrated Learning initiatives. To assist with the process of introducing necessary changes in the style of teaching or the layout of the course using feedback, this paper introduces a pipeline to achieve this by applying the streaming technology of Kafka developed in the field of Big Data along with filtering and summarization supported by BART and BERT.