https://github.com/tommygrammar/smart-business-copilot
My Smart Business Copilot
https://github.com/tommygrammar/smart-business-copilot
Last synced: 8 days ago
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My Smart Business Copilot
- Host: GitHub
- URL: https://github.com/tommygrammar/smart-business-copilot
- Owner: tommygrammar
- License: mit
- Created: 2025-04-14T08:45:40.000Z (about 1 month ago)
- Default Branch: blackgrammar-projects
- Last Pushed: 2025-05-12T19:34:17.000Z (10 days ago)
- Last Synced: 2025-05-12T20:47:25.879Z (10 days ago)
- Language: Python
- Size: 599 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: Readme.MD
- License: LICENSE
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README
# Computational Business Analyst
Computational Business Analyst is a high-performance decision intelligence system designed to help businesses understand operational dynamics, forecast future states, and make optimized strategic decisions. This repository provides a suite of computational models and data pipelines for business diagnostics, financial forecasting, and scenario analysis.
## Table of Contents
* [Overview](#overview)
* [Features](#features)
* [Installation](#installation)
* [Usage](#usage)
* [Directory Structure](#directory-structure)
* [Models Overview](#models-overview)
* [API Endpoints](#api-endpoints)
* [Contributing](#contributing)
* [License](#license)
## Overview
This repository integrates a broad set of models designed to generate interpretable, data-driven insights. Key functionalities include:
* Sensitivity analysis and simulation of business scenarios.
* Forecasting of cash flow, sales, and growth metrics.
* Competitive landscape analysis and strategy impact evaluation.
* Event probability estimation and product-level diagnostics.
## Features
* **Multi-Domain Inference**: Integrated model suite for operations, finance, and market behavior.
* **Forecasting & Risk Modeling**: Predictive modules for cash flow, demand, and exposure to risk events.
* **Strategic Diagnostics**: Tools for competitor response modeling and resource allocation optimization.
* **Product & KPI Segmentation**: Event probability analysis and performance clustering across products and KPIs.
* **RESTful API Access**: Flask-based endpoints for seamless integration and modular use.
## Installation
Clone the repository and install dependencies:
```bash
git clone https://github.com/tommygrammar/smart-business-copilot.git
cd smart-business-copilot
pip install -r requirements.txt
```
## Usage
Start the Flask API server:
```bash
python api.py
```
Use tools such as `curl` or Postman to send requests to model endpoints. Refer to the [API Endpoints](#api-endpoints) section for route details.
## Directory Structure
```bash
smart-business-copilot/
├── Data/
│ └── business_data.py # Business-specific data handling scripts
├── Models/
│ ├── business_twin_sensitivity_model.py
│ ├── competitor_analysis.py
│ ├── demand_analysis.py
│ ├── event_probability_models.py
│ ├── gradient_ascent_sensitivity_allocation_model.py
│ ├── growth.py
│ ├── risk_model.py
│ ├── sales_forecast.py
│ └── ... # Additional analytics models
├── api.py # Flask API to expose model functionality
├── requirements.txt # Python dependency list
```
## Models Overview
### 1. Business Twin Sensitivity Model
* **File**: `Models/business_twin_sensitivity_model.py`
* **Purpose**: Simulates business dynamics to evaluate how input changes affect outcomes.
* **Application**: Sensitivity testing for core KPIs under different operational assumptions.
### 2. Competitor Analysis
* **File**: `Models/competitor_analysis.py`
* **Purpose**: Applies Bayesian inference to model and assess competitor strategies and their influence.
* **Application**: Evaluating relative market positioning and expected competitive response.
### 3. Demand Analysis
* **File**: `Models/demand_analysis.py`
* **Purpose**: Forecasts product-level demand over time horizons using historical patterns and external signals.
* **Application**: Planning inventory, marketing, and production in alignment with projected demand.
### 4. Event Probability Models
* **File**: `Models/event_probability_models.py`
* **Purpose**: Quantifies likelihoods of predefined business events using statistical modeling.
* **Application**: Anticipating disruptions or inflection points (e.g., stockouts, customer churn).
### 5. Growth Models
* **File**: `Models/growth.py`
* **Purpose**: Projects growth trajectories, interactions between KPIs, and systemic behavior over time.
* **Application**: Long-term planning, target setting, and monitoring early warning indicators.
### 6. Sales Forecasting
* **File**: `Models/sales_forecast.py`
* **Purpose**: Predicts sales volumes across short- and medium-term windows.
* **Application**: Revenue planning, pricing strategy, and supply chain coordination.
### 7. Risk Analysis
* **File**: `Models/risk_model.py`
* **Purpose**: Estimates probability and impact of business risks using scenario-based methods.
* **Application**: Operational continuity planning and mitigation strategy design.
*(Additional models can be found in the Models directory.)*
## API Endpoints
Each model is exposed as a RESTful endpoint via the Flask API. Example routes:
| Endpoint | Method | Description |
| ------------------- | ------ | ------------------------------------------------------------ |
| `/twin` | POST | Run Business Twin sensitivity simulation. |
| `/cashflowsales` | POST | Analyze weekly cash flow and sales activity. |
| `/competitorimpact` | POST | Assess strategic influence of competitors. |
| `/demand` | POST | Forecast product-level demand. |
| `/eventprobability` | POST | Compute likelihoods of business-critical events. |
| `/optimize` | POST | Perform resource allocation via gradient-based optimization. |
| `/growth` | POST | Simulate growth paths and KPI interaction. |
| `/salesforecast` | POST | Generate forward-looking sales forecasts. |
Detailed implementation is provided in `api.py`.
## Contributing
To contribute, follow the standard development workflow:
1. Fork this repository.
2. Create a new feature branch:
```bash
git checkout -b my-feature-branch
```
3. Make your changes and commit:
```bash
git commit -am "Add feature or fix"
```
4. Push to your fork and submit a pull request:
```bash
git push origin my-feature-branch
```
## License
This project is licensed under the MIT License. See the `LICENSE` file for full terms.