I successfully automated a manual message review process for Contra, a marketplace connecting companies with freelance workers. By fine-tuning an OpenAI model, I achieved an accuracy of over 75% in approving or denying messages and flagging others for review. The implementation also included confidence scores to allow manual review when the model's certainty was not high.

The goal of this project was to streamline the message review process on Contra's platform. Previously, team members manually reviewed certain messages exchanged between companies and freelancers. This task consumed a significant amount of time and effort. To overcome this challenge, I utilized my expertise in natural language processing (NLP) and machine learning to train an OpenAI model specifically designed for message classification. By leveraging a labeled dataset provided by Contra, I fine-tuned the model using various techniques. The final solution incorporated confidence scores generated by the model, allowing team members to prioritize their focus on messages that required human intervention. The system seamlessly integrated into contra's existing infrastructure without any disruptions.

By successfully automating the message review process on contra's platform through fine-tuning an OpenAI model with confidence scoring capabilities, valuable time was saved, and operational efficiency was enhanced. This case study demonstrates my ability to leverage advanced NLP techniques and machine learning to address real-world challenges. If you're seeking a skilled professional who can optimize your platform's communication workflows, I'm confident that my expertise will deliver exceptional results.