This is a submission for the Gemma 4 Challenge: Build with Gemma 4
CrisisIQ – AI-Powered Crisis Intelligence & Business Risk Analysis Dashboard
What I Built
CrisisIQ is an AI-powered business intelligence dashboard that analyzes how global crises impact companies, industries, and supply chains in real time.
Modern companies operate in highly interconnected ecosystems where geopolitical conflicts, cyberattacks, economic instability, sanctions, natural disasters, and trade disruptions can rapidly affect operations worldwide. CrisisIQ helps users understand these impacts using AI-driven analysis and contextual reasoning.
The platform allows users to:
- analyze company exposure during crises
- understand operational and financial risks
- simulate business disruption scenarios
- generate AI-powered mitigation strategies
- summarize complex global events into actionable insights
Instead of manually reading lengthy reports and news articles, users receive structured AI-generated intelligence instantly.
Demo
Features Demonstrated
- Company risk analysis dashboard
- Crisis impact summarization
- AI-generated mitigation strategies
- Scenario simulation
- Industry-wise risk comparison
- Supply chain disruption analysis
Demo Video
https://drive.google.com/file/d/1kMt-lclhDu2YvFDQi1mgjPbBoagkEouq/view?usp=drive_link
Live Project
https://crisisiq-ai-business-risk-intelligence-using-gemma-4-edaputmky.streamlit.app/
Screenshots
Code
GitHub Repository
https://github.com/Tanya-garg10/CrisisIQ-AI-Business-Risk-Intelligence-using-Gemma-4.git
Tech Stack
- Python
- Streamlit
- Gemma 4
- Pandas
- Plotly
- OpenRouter / Google AI Studio API
- News APIs
How I Used Gemma 4
Gemma 4 powers the core reasoning engine of CrisisIQ.
The application collects company data, industry context, and crisis-related information, then uses Gemma 4 to generate intelligent business impact analysis.
Model Used
Gemma 4 31B Dense
Why I Chose the 31B Dense Model
I intentionally selected the 31B Dense model because the project depends heavily on:
- long-context understanding
- analytical reasoning
- structured business analysis
- multi-factor risk interpretation
The larger context window allowed the model to process:
- lengthy crisis reports
- multiple company profiles
- supply chain dependencies
- geopolitical developments
This made the 31B Dense model the ideal choice for generating detailed and reliable business intelligence insights.
How Gemma 4 Powers the System
Gemma 4 analyzes:
- crisis events
- company operations
- industry dependencies
- supply chain vulnerabilities
- financial exposure
The model then generates:
- risk assessments
- operational impact summaries
- mitigation recommendations
- scenario-based predictions
- executive-level insights
Example Output
“The ongoing geopolitical conflict may significantly disrupt semiconductor supply chains affecting manufacturing timelines and increasing operational costs for automotive companies dependent on Asian suppliers.”
The system transforms raw crisis information into understandable strategic intelligence.
Key Features
AI Risk Scoring
Generates dynamic company risk scores based on current events.
Crisis Summarization
Converts complex news and reports into concise business insights.
Scenario Simulation
Allows users to test hypothetical crisis situations and predict business outcomes.
Supply Chain Intelligence
Identifies vulnerable operational dependencies and potential disruption points.
Executive Insights
Produces human-readable strategic recommendations for decision-making.
Challenges I Faced
One of the main challenges was designing prompts that produced structured, analytical responses instead of generic summaries.
Another challenge was handling large volumes of contextual information while maintaining coherent reasoning and fast response times.
Balancing accuracy, readability, and practical usefulness required significant prompt engineering and response optimization.
What I Learned
Through this project, I gained deeper experience in:
- AI-powered reasoning systems
- long-context prompt engineering
- business intelligence workflows
- risk analysis pipelines
- dashboard development
- integrating LLMs into analytical applications
I also learned how powerful open models like Gemma 4 can be for enterprise-style AI applications.
Future Improvements
Planned future enhancements include:
- real-time live news integration
- predictive trend forecasting
- interactive crisis maps
- AI-generated financial impact estimation
- multilingual analysis support
- collaborative enterprise dashboards
Final Thoughts
CrisisIQ demonstrates how AI can transform overwhelming global information into actionable strategic intelligence.
By combining real-world crisis data with the reasoning capabilities of Gemma 4, the platform helps businesses better understand risks, prepare for disruptions, and make informed decisions faster.
This project highlights the growing potential of open AI models in enterprise intelligence and decision-support systems.
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