Prathiba Lakshmi

• Built an AI chatbot using Dialogflow, FastAPI, and MySQL, enabling 5K+ monthly QR-based issue reports and auto-categorization across 6 platforms.
  Integrated CV for severity analysis, reducing manual triage time by 40%.
• Delivered MVP in 6 weeks using Agile, leading sprints and stakeholder reviews for fast feedback.
  Launched predictive maintenance and voice NLP features, improving resolution time by 30%.
• Architected scalable microservices with NiFi, Airflow, Power BI, and RBAC, enabling real-time ops tracking.
  Integrated ERP/CRM systems, boosting task assignment efficiency by 50%.

• Spearheaded cutting-edge chatbots leveraging RAG techniques
• Implemented PDF text chunking and cleaning processes using Python, langchain, and regex for effective knowledge extraction from research papers
• Engineered robust user query classification model achieving 98% accuracy with BERT
• Integrated pre-trained Large Language Models (LLM) such as Jina V2 and GPT-3.5 Turbo for prompt engineering, answer generation, and embedding generation stored in Pinecone VectorDB index
• Conducted retrieval and generation evaluations using pandas, ensuring high accuracy of chatbots's responses

• Developed and fine-tuned predictive models, including Logistic Regression and Neural Network, for Breast Cancer Prediction, achieving a 92% increase in accuracy and enhancing predictive capabilities for early detection
• Attained accuracy rate of 92% in predictive performance that aids in early breast cancer detection or risk assessment
• Reduced overfitting in ML models by applying regularization techniques and systematically evaluating model complexity.

• Scraped and structured data from 500+ Amazon product pages using BeautifulSoup and Selenium, capturing over 10,000+ customer reviews and product attributes. Stored data in PostgreSQL for structured querying, enabling 95% faster access to key insights for analysis.
• Applied SMOTE to balance class labels across 5,000+ records, engineered features using scikit-learn, and developed a custom FCNN in PyTorch achieving 87% prediction accuracy in identifying product relevance for specific user needs improving recommendation precision and guiding stock strategy through POC implementation.

Bank Loan Analysis

• Developed an interactive Power BI dashboard by extracting and transforming data using SQL queries from a bank loan dataset of 10,000+ records. Visualized key metrics such as loan approval rate, default rate, and credit score distribution, improving risk analysis and enabling 15% better decision accuracy.
• Utilized SQL for complex data filtering and joins, and performed detailed loan trend analysis to uncover insights into demographic patterns, repayment behavior, and high-risk segments, contributing to an 8% reduction in loan defaults through data-driven policy recommendations.

• Tutored over 300 students in various IT subjects and Soft Skills and Communication training, achieving success rate of over 90%
• Designed & delivered training modules across diverse skills across various age groups with average satisfaction rating of 93%
• Provided one-on-one mentoring to help individuals reach their full potential within the organization.

• Achieved year-on-year scale up of 40% growth and student success rate
• Transformed Matriculation curriculum with data analytics, elevating student engagement and retention by up to 25%