Developed a comprehensive AI-driven web-based application using React and Python’s Langchain framework to process user-uploaded documents (PDF, Word) and images to extract text and provide context-aware responses.Segmented text into manageable chunks and generated vector embeddings using OpenAI’s embeddings, storing them in a MongoDB cluster.Implemented a MongoDB Atlas vector search index using PyMongo for efficient querying and enabled users to interact with their own data through Langchain’s Retrieval Augmented Generation (RAG) functionality.Utilized GPT-3.5 turbo Large Language Model within Langchain containers communicated via RESTful API calls and employed prompt templates for dynamic user responses.Integrated FastAPI to run Python services on Uvicorn servers and connected the backend services to a React-based frontend for a seamless user experience, enabling document and image uploads for processing.Developed the user-friendly registration page with form validation, storing user information securely in MongoDB.Created a sign-in page that uses JWT-based authentication for secure session handling.Built a dashboard using Spring controllers and services to monitor real-time usage statistics, including active users and login tracking by collecting IP addresses.Leveraged React hooks such as useState and useEffect for real-time updates and chat functionality within the interface.Utilized useReducer for complex state management, particularly in handling multi-step workflows.Integrated useContext and custom hooks for managing shared states like user authentication and session data globally, improving code readability.Handled communication with the backend using Axios for asynchronous HTTP requests, utilizing async/await syntax for smoother code with enhanced error handling.Optimized the initial loading time of the application through lazy loading components with React.lazy and Suspense, loading only what’s necessary.

• Designed Tableau Dashboards to display required KPIs as per business requirements.• Developed and tweaked SQL queries for mining data from SQL server DB.• Set up Automations using SQL and Python, established segments in the Salesforce CRM to track data flow according to business rules.• Modelled data in the staging database and validated data in SQL Server Management Studio.• Developed email campaigns using HTML in the Salesforce Marketing cloud and increased the targeted reach by 80%.• Crafted Playbook and established campaign and email metadata using internal tools.• Customized HTML emails for each campaign, configured custom tags for Unsubscribes, Personalization, CTA, UTMs.• Imported contacts from clients or created segments from the database based on affiliations/specialties.• Generated Ad-hoc/Scheduled tracking reports for Email/Journey campaigns to report necessary KPIs

Study on design and manufacture of Turbo alternators