Case Study

UI with Feedback Mechanism for LLM Seamless Interactions with Scientific Users

Our team undertook the challenge of enhancing the interaction between scientists and Language Models from OpenAI. The existing system lacked a user-friendly front-end interface for scientists to provide feedback on the model’s answers, hindering the iterative improvement process.


Collaborating with a UX/UI designer, we created wireframes and design concepts, incorporating feedback from the team and stakeholders. The front-end development phase utilized modern web technologies, resulting in a responsive and user-friendly UI that seamlessly integrated with the LLM. The integration process involved close collaboration with the Data Scientist team responsible for the LLMs. We established robust communication channels between the UI and the language model, implementing API endpoints and mechanisms for fetching model responses. Additionally, we incorporated a feedback mechanism, allowing scientists to provide valuable insights on the model’s answers.


The successful execution of this project significantly enhanced the workflow of researchers. The newly implemented UI facilitated seamless interaction with the LLM, enabling scientists to provide feedback effortlessly. The intuitive design and responsive interface improved the overall user experience, making it easier for scientists to navigate and interact with the language model. The integration of a feedback mechanism proved to be instrumental in refining the accuracy of the LLM over time. Scientists reported increased efficiency in providing specific insights and corrections to the model’s responses.