AI Sprint Risk Analyzer 🚀

Live App:
https://ai-sprint-risk-analyzer-jcqfd4z4habsx6uuactvep.streamlit.app/

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Overview

SprintRisk AI is a flexible, universal Streamlit app for sprint risk analysis. It allows project managers to upload any CSV file, map columns, and analyze sprint risks across tasks, blockers, and progress metrics. The app calculates risk levels, generates visual dashboards, and provides actionable insights, regardless of dataset structure.

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📊 Dashboard Preview

Sprint Risk Dashboard

Progress Metrics Summary

Risk Distribution Graph

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🎯 Key Features

✅ Upload any CSV file (from Jira, Excel, or custom sprint trackers)
✅ Flexible column mapping for Ticket ID, Task Description, Blockers, and Progress
✅ Optional fields: blockers and progress can be omitted
✅ Automatic risk detection: High / Medium / Low
✅ Risk distribution visualization
✅ Blocker tracking
✅ Sprint health score calculation
✅ Progress monitoring
✅ Download CSV with calculated risk

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🧠 How Risk Is Calculated

Risk levels are determined using task progress and blockers:

• High Risk → Blockers present AND progress below 50%
• Medium Risk → Blockers present OR progress below 50%
• Low Risk → No blockers AND progress ≥ 50%

Sprint Health Score is calculated based on:

• Low Risk Tasks → High contribution
• Medium Risk Tasks → Moderate contribution
• High Risk Tasks → Low contribution

This produces an overall percentage showing sprint stability.

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🛠️ How to Map Your Columns

When uploading a CSV, the app will prompt you to map:

Field	Description
Ticket ID	Unique task identifier (Task ID, Issue ID)
Update Text	Task description (Summary, Title, Task Name)
Blockers	Number of blockers (optional)
Progress	Task completion percentage (optional)

Notes:

• If blockers or progress are missing, the app will use default values:

  • Blockers = 0
  • Progress = 50%

• This ensures analysis and graphs remain accurate for any dataset.

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📂 Sample Input Format

Example CSV structure:

ticket_id,progress,blockers
ENG-101,40,1
ENG-102,90,0
ENG-103,60,0

📈 Sprint Metrics Included

The dashboard calculates:

• Total Tasks
• High Risk Tasks
• Medium Risk Tasks
• Low Risk Tasks
• Total Blockers
• Average Progress (%)
• Sprint Health Score (%)

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⚙️ Technologies Used

• Python
• Pandas
• Matplotlib
• Streamlit
• PIL (Python Imaging Library)

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▶️ How to Run Locally

Step 1 — Install dependencies: pip install streamlit pandas matplotlib pillow Step 2 — Run the app: streamlit run sprintrisk_app.py

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🚀 Future Enhancements

• Smart column auto-detection
• NLP-based risk analysis
• Jira API integration
• Predictive sprint risk modeling
• Multi-project dashboards

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👤 Author

Kathy Raina
AI & Product-Focused Project Developer