Prince Joshi's Work | ContraWork by Prince JoshiPrince Joshi
Full-Stack Developer building web apps and AI solutions.
SOP Automation — AI-Assisted SOP Generation
SOP Automation is a document-driven application designed to streamline the creation and management of Standard Operating Procedures (SOPs). It helps structure SOP content into predefined sections, process source documents, and support a more organized drafting and review workflow.
As a Full-Stack Developer at NLL Academy, I contribute to developing the application’s frontend, backend APIs, document-processing workflows, and database integrations.
Key contributions:
-Developed and integrated frontend features using React.js and TypeScript.
-Built and maintained backend APIs using Python and FastAPI.
-Worked on document-processing workflows for extracting and organizing content from Word documents and other supported formats.
-Implemented SOP section mapping and integration with predefined structure definitions.
-Worked on draft state management and saving generated SOP content.
-Contributed to SME guidance features that support the refinement of SOP drafts.
-Troubleshot API, database, and document-processing issues to improve application reliability.
Tech stack: React.js, TypeScript, Python, FastAPI, PostgreSQL, SQLAlchemy, and Docling.
The project has given me practical experience building document-centric business applications, integrating complex backend workflows, and developing tools that help streamline structured business processes. Lira is an AI-powered knowledge assistance platform that helps users find reliable answers from internal documents using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).
As a Full-Stack Developer at NLL Academy, I contributed to building and integrating features across the platform, combining modern frontend experiences with backend APIs and AI-powered workflows.
Key contributions:
- Developed responsive user interfaces using React.js, TypeScript, and Tailwind CSS.
- Integrated frontend components with backend APIs built using Python and FastAPI.
- Contributed to document-based question-answering workflows powered by LLMs and RAG.
- Worked on guided learning experiences, learning paths, and conversational interactions.
- Contributed to analytics dashboards and data visualizations for monitoring platform usage.
- Collaborated on debugging, feature integration, and improving overall application usability.
Tech stack: React.js, TypeScript, Tailwind CSS, Python, FastAPI, REST APIs, LLMs, RAG, and SQL.
The project gave me practical experience building AI-enabled software that combines document retrieval, conversational interfaces, and full-stack application development.