Created a chatbot using RAG(Retrieval-Augmented Generation), OpenAI GPT-4o AI, vector embedding, Atlas MongoDB, and WebSocket, reducing resolution time for common user queries by 30%.

Developed a referral system using web browser cookies to store the token, increasing the client base by 20%.

Improved Information Retrieval features with Gemini 1.5 pro AI by using concurrent processing and sending all the Api requests all at once, reducing the latency by 2x.

Wrote technical documentation for the code base and made the onboarding process 2x faster.

Enhanced document filtration feature using Gemini 1.5 pro AI that filtered out unnecessary pages from the user’s legal document, reducing document review time for attorneys by 30%.

Optimized LLM’s prompts to reduce the total cost for each API request.

Engineered a multi-document scanning and consolidation feature, reducing average user task completion time for uploading by 60%.

Designed and implemented RESTful API endpoints, streamlining data transactions between backend, frontend and PostgreSQL database

Containerized PostgreSQL using Docker for streamlining data storage and retrieval processes

Utilized Supertoken for authentication and session control, decreasing developer time spent on authentication by 80%

Wrote unit and integration tests using JEST, improving application test coverage.

Submit report on research weekly.

Analyze the report and find the best way possible to work on project effectively and efficiently.

Collect necessary information to document the project and apply for grant.