BUD-AI is an AI-powered application that helps freelancers, project managers, and startups with project budgeting, forecasting, and optimization. It provides detailed cost breakdowns, suggests optimizations, and simulates different scenarios to help make informed financial decisions.
- Project Specification Parser: Analyzes project details including timeline, team composition, and required tools
- Budget Builder: Generates detailed cost breakdowns for personnel, tools, infrastructure, and more
- AI-Powered Optimizer: Suggests cost-saving measures and alternatives
- Financial Forecaster: Projects burn rate, cash flow, and ROI
- Scenario Simulator: Allows "what-if" analysis by modifying project parameters
- Clone the repository:
git clone https://github.com/yourusername/bud-ai.git
cd bud-ai- Install dependencies:
pip install -r requirements.txt- Run the application:
python app.py- Launch the application and you'll see the Gradio interface
- Enter your project details:
- Project Name
- Duration
- Team Roles
- Tools List
- Target Budget
- Estimated Revenue
- Click "Analyze Project" to generate:
- Budget Breakdown
- Optimization Suggestions
- Financial Forecast
- Cost Distribution Chart
- Cash Flow Projection
project_finance_planner/
│
├── agents/
│ ├── project_input_agent.py
│ ├── budget_builder_agent.py
│ ├── optimizer_agent.py
│ ├── forecast_agent.py
│ └── scenario_sim_agent.py
│
├── utils/
│ ├── data_parser.py
│ └── financial_calculations.py
│
├── app.py
├── prompts.py
├── example_inputs.json
└── requirements.txt
- ProjectInputAgent: Processes raw project input into structured information
- BudgetBuilderAgent: Maps roles and tools to costs using market rates
- OptimizerAgent: Suggests cost-saving measures and alternatives
- ForecastAgent: Projects financial metrics and assesses risks
- ScenarioSimAgent: Simulates different project scenarios
{
"project": "Launch MVP for AI fitness coach app",
"duration": "3 months",
"team": [
"1 UI/UX Designer",
"2 Developers",
"1 PM"
],
"tools": [
"Figma",
"Firebase",
"Stripe",
"Vercel"
],
"target_budget": "20000",
"estimated_revenue": "30000"
}- Gradio: For the web interface
- Pandas/Numpy: For data processing
- Plotly: For visualizations
- Python-dotenv: For environment variables
- Anthropic/Mistral: For AI-powered analysis
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License - see the LICENSE file for details.