• Minal Tushar Chaudhari
• Aditya Kalbhor
• Dr. Leena Deshpande

Artificial intelligence is used in the project called the 'Smart Invoice Query Analyzer' for making the data in invoices easily understandable with or without recognizing the dialect involved. Such a Streamlit interface provides image uploading and allows users to ask content-specific natural queries and receive answers in real time. The engine of this architecture is further confined by several other tools like LangChain for language modeling, proper effective data retrieval using ChromaDB and FAISS, as well as processing PDFs through PyPDF2. This architecture uses a Gemini 1.5 Flash model from Google Generative AI capable of efficient visual question answering. This entire arrangement makes it easy to read and comprehend bills either in picture format or in text format.

Smart Invoice Query Analyzer, Streamlit, Google Generative AI, Gemini 1.5 Flash, Vision-Based Question Answering, Invoice Image Processing, Natural Language Understanding (NLU), Document AI, LangChain, ChromaDB, FAISS, PyPDF2, AI Automation, Data Retrieval, Business Optimization.

"Smart Invoice Query Analyzer", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 11, page no.f605-f610, November-2024, Available :http://www.jetir.org/papers/JETIR2411570.pdf

"Smart Invoice Query Analyzer", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 11, page no. ppf605-f610, November-2024, Available at : http://www.jetir.org/papers/JETIR2411570.pdf