FileSense AI
AI document intelligence system for chat-based, context-aware insights
- LLMs
- RAG
- Vector Databases
- Embeddings
- Python
- Streamlit
- NLP
FileSense AI is an intelligent document query platform designed to convert static files into interactive knowledge sources. Users can upload documents in formats such as DOCX, PDF, Excel, or CSV and interact with them through natural language conversations. By combining large language models with vector-based retrieval, the system ensures responses remain grounded in the uploaded content, delivering accurate and reliable answers.
The system is built using a Python backend with a Streamlit-based frontend for fast iteration and smooth user interaction. Uploaded documents are parsed, chunked, and stored in a vector database using embeddings, enabling semantic search and efficient retrieval. FileSense AI also supports multiple LLMs, allowing flexible model selection based on accuracy, latency, or cost—making it ideal as a proof-of-concept for scalable document intelligence solutions.
Key Features
Interactive Document Chat
Ask questions and receive accurate answers based strictly on the document’s content.
Multi-File Format Support
Works seamlessly with PDF, DOCX, Excel, and CSV files.
Multi-Model LLM Support
Choose between different LLMs for response generation.
Vector Database Storage
Enables fast and semantic document retrieval using embeddings.
Targeted Text & Data Extraction
Pull specific sections, tables, or values using natural language queries.
The Problem
Important information is often buried inside long, unstructured documents, making it difficult and time-consuming to locate relevant insights. Traditional keyword search lacks contextual understanding, forcing users to manually scan files and increasing the risk of missed or misunderstood information.
VS
The Solution
FileSense AI introduces an AI-driven document querying experience powered by retrieval-augmented generation. Users can ask natural language questions and receive precise, context-aware answers extracted directly from the uploaded files, significantly reducing manual effort and improving decision-making speed.
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