LALIT WALE

Master's

Mechanical Engineering

Procter and Gamble

Machine Learning Engineer

- Smart, Automated, AI-Driven Registration (SAAR - Created a software solution to automate and streamline the regulatory dossier creation process for the approval of different types of pharmaceutical products at Procter and Gamble - Utilized Python, Streamlit, HTML, and CSS for application development. PDF data extraction was facilitated by EASYOCR, while PDF summaries were generated using Langchain and Hugging Face. The LLM model - Achieved a time-saving estimate of 6400 man-hours with the deployment of the application in Latin America - GenX PDF Extractor - Also, devised a vendor registration system employing MySQL, Streamlit, HTML, and CSS, to enable the efficient uploading of various vendor PDFs onto a unified platform - Pioneered a novel method for extracting data from PDFs, allowing users to select data coordinates using - EASYOCR. Leveraged those coordinates to extract data from numerous analogous PDFs. Built a dashboard for data visualization and analysis utilizing Pandas, Matplotlib, and Seaborn - Through cross-sector collaboration with experts in different sectors like pharmaceuticals, manufacturing, and software, we engineered a product that mitigated the issues in the former registration and analysis process