Scalable Document Query Assistant Using Ai and Cloud-Based Infrastructure

The proliferation of digital documents today is challenging in finding contextually relevant information. This study introduces a Document Query Assistant that exploits AI and cloud-based services to deliver rapid, exact, and contextually aware answers to user questions. The approach combines the Google Gemini NLP engine, Google Generative AI Embeddings, and the Facebook AI Similarity Search (FAISS) vector database along with Google cloud resources like Firebase and Google Drive allowing the knowledge base to be refreshed automatically and user interaction to be maintained in real-time. This achieves scale and efficiency. This approach outperforms the latest keyworddriven systems by achieving up to 92 % precision in test cases while managing multiple file formats (PDF, DOCX, CSV) via semantic search and cloud integration innovations.