AI Research Intelligence Platform: A Multi-Modal Document Analysis and Code Intelligence System

Abstract - This paper presents the AI Research Intelligence Platform, a comprehensive web-based application built on Streamlit that integrates natural language processing, semantic vector search, and code intelligence into a unified research assistance ecosystem. The platform supports multi-format document ingestion (PDF, DOCX, TXT), semantic indexing via ChromaDB using the SentenceTransformer all-MiniLM-L6-v2 model, conversational question-answering, extractive summarization, auto-generated multiple-choice quizzes, cross-document comparison, and multi-language code analysis with real-time execution and quality scoring. The system operates entirely on local CPU resources without external API dependencies, ensuring data privacy and reproducibility. Experimental results demonstrate 82% Q&A accuracy, ROUGE-1 of 0.48 for summarization, and 0.79 Spearman correlation for code quality scoring, confirming the system as an effective and cost-efficient research productivity tool. Key Words: Semantic Search, ChromaDB, SentenceTransformer, Streamlit, Document Intelligence, Code Analysis, NLP.