CompareWise AI is an offline-first, enterprise-grade procurement intelligence platform built to automate the extraction, analysis, and comparison of complex vendor proposals.
By leveraging local Large Language Models (LLMs) via Ollama, CompareWise AI completely eliminates the data privacy risks associated with cloud APIs. It allows procurement teams to extract pricing, timelines, SLAs, deliverables, and hidden risk clauses from PDF, DOCX, and XLSX files securely on their own hardware.
- 100% Offline & Private: Powered by Ollama (
llama3.2), ensuring sensitive enterprise vendor data never leaves your machine. No API keys or cloud costs required. - Smart Metric Extraction: Semantically extracts specific data points (Cost, Timeline, Deliverables) regardless of how the vendor formatted their proposal.
- Risk Clause Detection: Automatically flags unfavorable termination clauses, hidden fees, or weak liability caps.
- Executive Comparison Engine: Generates a side-by-side matrix, pros/cons list, and a definitive AI recommendation.
- Intelligent File Caching: Remembers previously uploaded files using MD5 hashing to return instant results (0.01s) on repeat uploads.
- Multi-Format Support: Drag and drop
.pdf,.docx, and.xlsxfiles simultaneously. - Premium UI: Features a sleek, responsive Glassmorphism design with seamless Light/Dark mode toggling.
- Python 3.9+ installed on your system.
- Ollama installed and running on your local machine.
- The
llama3.2model downloaded in Ollama (ollama run llama3.2).
- Clone this repository:
git clone https://github.com/yourusername/CompareWiseAI.git cd CompareWiseAI - Create a virtual environment:
python -m venv venv source venv/bin/activate # On Windows use: venv\Scripts\activate
- Install the dependencies:
pip install -r requirements.txt
To start the backend server and serve the frontend, run:
uvicorn main:app --host 127.0.0.1 --port 8000 --reload(Or simply run the included run.ps1 script if you are on Windows PowerShell).
Once running, open your browser and navigate to: http://127.0.0.1:8000
- Backend: Python, FastAPI, Uvicorn
- AI Processing: Ollama (Local LLM Integration)
- Frontend: Vanilla HTML, CSS (Glassmorphism), JavaScript
- Document Parsing: PyPDF2, python-docx, pandas, openpyxl
This project was specifically engineered for enterprise use cases where data privacy is paramount. Because it uses local inference, you can confidently process confidential pricing and legal documents without violating corporate data sharing policies.