Tanmay Sharma

• Project 1: HR Chatbot
  Tech Stack: Python, OpenAI, Llama CPP, Chroma DB
  Description: I developed a portal for our HR department that allows employees to search all company policy documents regarding referrals, leaves, insurance, etc. The chatbot provides personalized answers by using login credentials to retrieve real-time data about employees' leave status and working hours from the timekeeper platform.
• Project 2: Roofing Solutions
  Tech Stack: Python, Milvus DB, Towhee, Semantic Search
  Description: For a US-based roofing solutions company, I created an AI system to help their architects and designers become more productive. The system automates the creation of legal submittal documents, often related to previous jobs. Additionally, I implemented a recommendation system that suggests specific roofing industry products by analyzing current jobs and matching them with previous records.
• Project 3: Automobile Chatbot for BMW Australia
  Tech Stack: Vanna.ai, LlamaIndex, LangGraph
  Description: I enhanced an existing BI portal by developing a chatbot that answers general queries about automobiles and BMW. The chatbot accesses structured data from the client in a SQL server. Using LangGraph, the AI agent can retrieve relevant data and then proceed with answering the client's query. I also added a feature that generates interactive graphs for users who request visualizations of various parameters.
• Project 4: A Parametric Interface for Teachers
  Description: I created a portal where teachers can input various parameters, such as the number of children present, age, and duration, to generate an activity plan. The system provides links to required products, learning outcomes, and guidance on handling potential issues related to the activity.
• Project 5: Employee Review-Based Upskilling Course Recommendations. Description: I deployed a system using my company's employee rating portal, which recommends courses and areas for improvement. By considering various parameters, such as numerical ratings, verbal feedback, and ratings from seniors and juniors, this system collaborates with an upskilling client to enhance employee development.

Actively participated in diverse data science projects, including prediction,

Visualization, deep learning, and machine learning.

Utilized tools like Jupyter Notebook to contribute to the development and

implementation of predictive models

Harnessed machine learning techniques to extract valuable insights from data and

create visually compelling representations

Gained comprehensive understanding of the dynamic field of data science through

hands-on experience

Carried out data mining of 50+ web pages using Python frameworks

Generated a large directory of 1k+ FAQs for an AI-powered coding interview solution

Calculated weighted sentiment to classify news using NLP tools

Worked on an automated code testing environment for candidate skill assessment

Developed 11 projects based on NLP, ML, prediction, and classification

• Led a team of 12 students to make a satellite for ISRO's student satellite launch program
• Conducted 4 model rocket launches to gather weather and pollution data.