CLARIFY Scoring System for AI Ideas

A Streamlit application to evaluate and prioritize AI ideas using the CLARIFY framework.

About CLARIFY

CLARIFY is a scoring framework with 7 key factors to evaluate AI ideas:

• Challenges & Constraints - How critical is this problem?
• Look at the Data - Do we have the right data to make this work?
• AI Capabilities Mapping - Is AI the best way to solve this?
• Reality Check - How feasible is this to build?
• Integration & Implementation - How well does this fit the platform?
• Future-Proofing & Timeline - Can this scale and remain valuable over time?
• Yield & ROI Estimation - What's the potential business impact?

Each factor is scored from 1-5, with higher scores indicating better suitability for AI implementation.

Features

• Score ideas across all 7 CLARIFY factors
• Visualize ideas on an effort vs. impact matrix
• Compare multiple ideas for prioritization
• Analyze individual ideas with radar charts showing all CLARIFY factors
• Tooltips with scoring criteria for each factor

Installation

1. Clone this repository:

git clone <repository-url>
cd CLARIFY-scoring

2. Install the required dependencies:

pip install -r requirements.txt

3. Run the application:

streamlit run clarify.py

Usage

1. Enter your AI idea name
2. Use the sliders to score each CLARIFY factor
3. Click "Add AI Idea" to save it
4. View all ideas in the table and visualization
5. Select individual ideas to view detailed factor analysis

Scoring Logic

• Impact Score: Sum of C, A, F, Y factors (max 20)
• Effort Score: 15 minus the sum of L, R, I factors (max 12)
• CLARIFY Average: Average of all 7 factors (max 5)

The quadrant chart helps prioritize ideas based on impact and effort:

• Quick Wins: High impact, low effort
• Strategic Investments: High impact, high effort
• Nice to Have: Low impact, low effort
• Avoid: Low impact, high effort