Automated the distribution of coaching requests for professional drivers, contributing to improved road safety by quickly and efficiently analyzing large amounts of data to deliver prompt and impactful coaching requests, cutting vast amounts of manual analysis and human error from the process

Developed an application utilizing embeddings to draw insight from LLMs about internal company metrics and data.

• Data processed in Azure Data Factory following medallion architecture

• Text embedded using OpenAI text-embedding-ada-002 model

• Natural language output and analysis provided by OpenAI gpt-3.5-turbo model

• Frontend app developed using React in Typescript with Yarn package management

QA testing for performance of conversational AI

Wrote Selenium tests in Scala to test training website

Explored the use of graph databases for knowledge storage on Neo4J