Kavinilavan Ravichandran

Ferma Chat Search Portal(ci.ferma.ai)

• SQLAlchemy ORM: Optimized database queries using SQLAlchemy ORM library.
• Pandas: Utilized Pandas library for data analysis, manipulation, and visualization purposes.
• Docker: We containerized and managed the Ferma-Chat portal, ensuring consistent, scalable environments across development and production.
• FastAPI: We developed and optimized the backend for Ferma-Chat, leveraging FastAPI to deliver high-performance APIs and asynchronous functionality.
• Elasticsearch: We integrated Elasticsearch into the Ferma-Chat platform, enabling real-time search and data retrieval across large user interactions.
• Jenkins: We automated the CI/CD pipeline for Ferma-Chat using Jenkins, streamlining the build, test, and deployment processes for continuous development.
• Developed multi-threaded programs by leveraging threading or multiprocessing modules of Python.
• Optimized neural networks to improve accuracy and speed of model performance.
• Performed data pre-processing, feature engineering, and hyperparameter tuning for deep learning models.

• PHP Frameworks (Laravel, Symfony): We utilized Laravel to build the Synapse data analytics portal, enhancing scalability and maintainability with design patterns and modular architecture.
• RESTful Web Services: We built RESTful APIs using Laravel, ensuring smooth data exchanges through JSON for various analytics tasks.
• SQL Queries & MySQL: We crafted and optimized complex SQL queries to handle survey analysis, interacting with the MySQL database to retrieve and process large datasets.
• Stored Procedures & Triggers: We developed stored procedures, functions, and triggers to meet the specific analytical needs of the portal, improving performance and automation.
• Queues for Long-Running Tasks: We implemented queues in Laravel to manage long-running data analysis, minimizing waiting times and improving user experience.

Claims Data Chat Interface

• Svelte & Python: We developed a claims data portal using Svelte for the front-end and Python for the back-end, ensuring a smooth, responsive user interface and robust data handling.
• Chat Interface with OpenAI: We integrated a chat interface powered by OpenAI, creating a dynamic user experience with real-time, AI-driven interactions.
• Prompt Engineering: We wrote and optimized prompts for the chat interface, enhancing the AI's responses and making the conversation more interactive and natural.
• Conversational History Tracking: We implemented conversational history tracking to provide a seamless, context-aware chat experience, allowing users to refer back to previous interactions.