Nov 2024 – May 2025 · 6 mos · Pune, Maharashtra, India · On-site

• Developed AI-powered chatbots using LLAMA, RAG, and ChromaDB to automate real-time insights and document-based queries, improving client interactions. This solution enabled seamless access to actionable data, enhancing customer satisfaction by 30% and reducing manual insight generation efforts by 60%.
• Engineered predictive models for inventory forecasting using time series analysis, including techniques like ARIMA, Prophet, and LSTM, to predict demand for products. The solution improved forecasting accuracy by 25%, enabling more efficient inventory planning and reducing stockouts and overstock scenarios.
• Designed and deployed NLP-based systems for warehouse complaint classification, automating the categorization of complaints into predefined categories. This system reduced resolution times by 80% and significantly increased delivery success rates, streamlining the workflow and improving operational efficiency.
• Implemented Generative AI solutions using the Agentic AI architecture, incorporating planning and memory modules along with Pandas CodeAgent to automate and enhance data-driven decision-making. This approach not only reduced manual efforts by 60% but also provided real-time, actionable insights to clients, improving decision accuracy.
• Proficient in TensorFlow, Hadoop, Spark, and Tableau, utilizing these technologies to build scalable machine learning models, process large datasets, and create impactful visualizations. These tools enabled the successful integration of advanced data science solutions into client platforms, improving data accessibility and operational insights.

Mar 2023 – Apr 2023 · 1 mo · India · On-site

• Conducted rigorous testing and analysis of cutting-edge algorithms for the OpenAl Whisper
• library, leading to the successful development of speech to text capabilities.
• Developed and implemented a live speech to text converter, handling more than 1 hour of audio
• data, achieving an impressive average accuracy rate of 75%.
• Significantly enhanced communication accessibility for individuals with hearing impairments by
• improving the accuracy and reliability of speech to text conversion.
• Produced a comprehensive and insightful case study on the effective integration of Artificial
• Intelligence (AI) and Machine Learning (ML) solutions across various industries, such as healthcare
• and finance.
• Demonstrated the potential impact of AI and ML on cost savings and efficiency improvements
• through real-life examples and relevant data analysis.
• Showcased an in-depth understanding of the practical implications and benefits of leveraging AI
• and ML technologies in diverse business contexts.

Mar 2022 – Jun 2022 · 3 mos

• Implemented deep learning models including convolutional neural networks, recurrent neural networks,
• and long short-term memory neural networks to analyze network-based intrusion detection
• systems (IDS) using support vector machines (SVM).
• Utilized confusion matrix, ROC curves, and AUC ROC curves to evaluate the performance of the
• deep learning model.
• Conducted secondary research on missile detection systems and applied machine learning
• models, specifically convolutional neural networks.
• Developed a chat application platform on XAMPP server, leveraging Ajax, PHP, HTML, JavaScript,
• and JQuery, to facilitate advanced technological exchange among DRDO personnel.
• Increased the discussion of technical problems by 40% through the implementation of the chat
• application platform.