Badri Mounika

Concord: LLM-Driven RecAI for Similar-Profile Product Discovery is an AI-powered recommendation system designed to provide personalized product suggestions through natural language conversations. Unlike traditional recommendation systems that rely on keyword matching, Concord understands user intent using Large Language Models (LLMs), semantic embeddings, and Retrieval-Augmented Generation (RAG). Product embeddings are generated using all-MiniLM-L6-v2 and indexed with FAISS for fast similarity search, while DuckDB stores and manages product data efficiently. LangChain and LangGraph orchestrate the intelligent recommendation workflow, and GPT-4o-mini generates explainable recommendations based on user preferences and retrieved products. The solution also supports budget and feature-based constraints, conversational follow-up queries, and dynamic filtering. Concord secured Third Place in the Innovate@CR Hackathon, showcasing the practical application of Generative AI and Agentic AI in re

IntelliRecommend is an AI-powered Product Recommendation Platform that helps businesses make data-driven inventory and merchandising decisions through intelligent recommendations and advanced analytics. The platform analyzes customer behavior, purchase history, product attributes, and sales trends to identify buying patterns, segment customers into meaningful clusters, forecast future demand, and recommend the most relevant products for each customer segment or store. It features an interactive dashboard with real-time KPIs, visual analytics, customer clustering, forecasting, and personalized recommendations. Built using Python, Machine Learning, and Generative AI concepts, the solution delivers actionable insights through a modern, responsive interface, enabling retailers to improve inventory planning, optimize product assortment, increase customer satisfaction, and drive sales growth while reducing manual decision-making.

• Lexora is an AI-powered Campaign Management Platform that helps businesses analyze, manage, and optimize digital marketing campaigns. It integrates data from Google Ads, Google Analytics 4 (GA4), and Ahrefs to provide comprehensive campaign insights. The platform features interactive dashboards, campaign performance analytics, budget optimization, forecasting, and AI-driven recommendations to improve marketing outcomes.
• As an AI Developer / Data Scientist, my role is to develop Machine Learning models and AI-powered analytics for the platform. My responsibilities include data preprocessing, feature engineering, exploratory data analysis (EDA), building predictive models, developing recommendation systems, and generating intelligent insights. These capabilities enable marketers to optimize campaign performance, improve budget allocation, maximize ROI, and make data-driven decisions efficiently through an intelligent and user-friendly platform.