AI Case Insights
Analyze cases automatically with AI-powered insights, patterns, and recommendations.
What are Case Insights?
Case Insights uses AI to analyze your cases and provide actionable intelligence:
- Key Issues Identification: Automatically detect main problems and themes
- Pattern Detection: Find similarities with historical cases
- Risk Analysis: Flag potential legal, financial, or operational risks
- Actionable Recommendations: Get specific next steps
- Historical Context: Learn from similar past cases
Why Use It?
Make Better Decisions:
- See patterns you might miss manually
- Learn from similar cases
- Identify risks early
Save Time:
- Instant case analysis (vs. hours of manual review)
- Auto-generate insights from documents
- Skip repetitive analysis work
Improve Outcomes:
- Act on AI-recommended next steps
- Avoid pitfalls from similar cases
- Prioritize highest-impact actions
How It Works
Analysis Process
1. You create or update a case
↓
2. Upload case documents and notes
↓
3. Request AI Insights
↓
4. AI analyzes:
- Case description
- All documents
- Timeline events
- Historical similar cases
↓
5. AI generates:
- Key issues and themes
- Patterns and trends
- Risk factors
- Actionable recommendations
What AI Analyzes
Case Data:
- Case description and title
- Status and priority
- Associated documents
- Timeline events
- Tags and categories
- Notes and comments
Document Content:
- Contracts and agreements
- Correspondence (emails, letters)
- Legal documents
- Financial records
- Evidence and attachments
Historical Context:
- Similar past cases
- Common patterns
- Success/failure factors
- Resolution approaches
Using Case Insights
Generate Insights for a Case
Steps:
- Open case in Journalist Mode
- Click AI Insights button
- Wait for analysis (10-30 seconds)
- Review insights report
Insight Report Includes:
📊 Case Insights: Government Corruption Investigation
Key Issues (5):
1. Payment irregularities in DoD contracts
2. Potential conflict of interest (Sen. Smith & XYZ Corp)
3. Whistleblower protection requirements
4. Evidence chain of custody
5. Publication timing and legal review
Themes (3):
- Public corruption
- Government contracts
- Whistleblower source protection
Patterns Detected:
- Similar to "Defense Contractor Fraud - 2022" case
- Common theme: kickback schemes via shell companies
- Historical success rate: 78% publication, 45% prosecution
Risk Factors (4):
⚠️ HIGH: Whistleblower identity exposure risk
⚠️ HIGH: Legal action by Sen. Smith (defamation)
⚠️ MEDIUM: Source document authenticity challenges
⚠️ LOW: Publication injunction attempt
Actionable Recommendations (6):
1. Priority: Verify wire transfer documents with independent forensic accountant
2. Legal: Request pre-publication legal review within 7 days
3. Security: Implement additional source protection measures
4. Evidence: Secure original documents in safe deposit box
5. Timeline: Complete investigation within 45 days (election cycle)
6. Backup: Brief backup reporter at partner publication
Similar Historical Cases (3):
- "Defense Contractor Fraud - 2022" (85% match)
- "Senate Ethics Violation - 2021" (72% match)
- "DoD Procurement Scandal - 2020" (68% match)
Confidence: 0.89 (High)
Generated: October 15, 2025 at 7:45 PM
Understanding Insights
Key Issues:
- Main problems or focus areas in the case
- Ranked by importance
- Extracted from documents and case data
Themes:
- Overarching topics or categories
- Help categorize and relate to other cases
- Useful for filtering and search
Pattern Detection:
- Similarities with past cases
- Common approaches that worked/failed
- Statistical success rates
Risk Factors:
- Potential problems or dangers
- Severity levels: HIGH, MEDIUM, LOW
- Proactive risk mitigation
Recommendations:
- Specific, actionable next steps
- Prioritized by impact
- Based on case analysis + historical patterns
Case Types and Insights
Investigative Journalism Cases
AI Analyzes:
- Source protection needs
- Evidence verification steps
- Legal review requirements
- Publication strategy
- Safety considerations
Example Insights:
Key Issues:
- Source anonymity preservation
- Document authenticity verification
- Legal exposure (defamation, injunctions)
Recommendations:
- Implement source protection protocol
- Engage defamation attorney for pre-pub review
- Establish backup reporter at partner org
- Create dead man's switch for materials
Legal Cases
AI Analyzes:
- Key legal issues and claims
- Evidence strength
- Relevant precedents
- Procedural deadlines
- Settlement potential
Example Insights:
Key Issues:
- Breach of contract (employment agreement)
- Wrongful termination claim
- Non-compete enforceability question
Recommendations:
- Review state law on non-compete clauses
- Gather evidence of performance reviews
- Consider mediation before litigation
- Document damages (lost wages, benefits)
Customer Support Cases
AI Analyzes:
- Issue category and severity
- Customer sentiment
- Resolution approaches
- Escalation triggers
- Similar case outcomes
Example Insights:
Key Issues:
- Account access locked
- Password reset not working
- Customer frustrated (3rd contact)
Recommendations:
- Escalate to Tier 2 support immediately
- Manual account unlock required
- Follow up with root cause analysis
- Offer service credit for inconvenience
Advanced Features
Pattern Detection
AI finds patterns across multiple cases:
Trend Analysis:
- "30% increase in account lockout cases this month"
- "Most common issue: password reset failures"
- "Average resolution time: 2.3 days"
Root Cause Identification:
- "Pattern: All cases involve users with 2FA enabled"
- "Likely cause: Bug in 2FA implementation"
- "Recommendation: Disable 2FA temporarily, patch bug"
Risk Scoring
AI assigns risk scores to cases:
Risk Categories:
- Legal Risk: Lawsuits, compliance violations
- Financial Risk: Monetary losses, refunds
- Reputational Risk: PR issues, customer churn
- Operational Risk: System downtime, data loss
- Security Risk: Breaches, unauthorized access
Risk Levels:
- Critical (9-10): Immediate action required
- High (7-8): Address within 24 hours
- Medium (4-6): Address within 1 week
- Low (1-3): Monitor, address as resources allow
Historical Comparison
Compare current case with similar past cases:
Similarity Factors:
- Case type and category
- Key issues and themes
- Entities involved
- Document types
- Outcomes
Learnings:
- What worked in similar cases?
- What didn't work?
- Average time to resolution
- Common pitfalls to avoid
Practical Examples
Example 1: Whistleblower Case
Scenario: Source provides leaked government documents.
AI Insights Generated:
Key Issues:
- Source identity protection (CRITICAL)
- Document authenticity verification
- Legal exposure assessment
- Safe publication strategy
Risk Factors:
⚠️ CRITICAL: Source exposure = life-threatening
⚠️ HIGH: Government injunction attempt
⚠️ MEDIUM: Document authenticity challenges
Recommendations:
1. Engage source protection expert immediately
2. Forensic analysis of leaked documents
3. Pre-publication legal review with First Amendment attorney
4. Establish international backup publication channels
5. Implement secure communication protocols (Signal, Tor)
Similar Cases:
- "NSA Whistleblower - 2013" (90% match)
→ Success: Published despite injunction
→ Lesson: Early legal counsel critical
- "Panama Papers - 2016" (85% match)
→ Success: International collaboration protected sources
→ Lesson: Partner with orgs in multiple jurisdictions
Action Taken:
- Followed all 5 recommendations
- Engaged First Amendment lawyer within 24 hours
- Established backup with Guardian UK
- Story published successfully, source protected
Example 2: Contract Dispute
Scenario: Client claims vendor breached service agreement.
AI Insights Generated:
Key Issues:
- Service level agreement (SLA) violations
- Financial damages calculation
- Breach remedies (termination vs. cure period)
Risk Factors:
⚠️ MEDIUM: Vendor disputes SLA interpretation
⚠️ LOW: Limited evidence of damages
Recommendations:
1. Document all SLA violations with timestamps
2. Calculate damages (service credits, lost revenue)
3. Review contract termination clauses
4. Send formal breach notice with 30-day cure period
5. Prepare for mediation or arbitration
Similar Cases:
- "SaaS Vendor Breach - 2023" (88% match)
→ Outcome: Settled in mediation
→ Resolution: 6 months service credits + contract term
extension
→ Lesson: Document everything, consider business relationship
Action Taken:
- Sent breach notice with documentation
- Vendor responded with service credits offer
- Negotiated settlement, preserved relationship
- Case closed in 45 days
Best Practices
When to Use Case Insights
✅ Good Use Cases:
- Complex cases with many documents
- Cases similar to past cases (learn from history)
- High-risk cases needing thorough analysis
- Cases where you're unsure of next steps
- Regular case reviews (weekly, monthly)
❌ Not Recommended:
- Very simple cases (single-issue, quick resolution)
- Cases with no documents (limited data for AI)
- Cases requiring immediate action (AI takes 30 seconds)
- Highly sensitive cases where AI review is inappropriate
Improving Insight Quality
Provide Good Data:
- Upload all relevant documents
- Write detailed case descriptions
- Maintain accurate timeline
- Tag cases appropriately
- Add notes and context
Update Regularly:
- Re-generate insights after major updates
- Review insights weekly for active cases
- Compare AI insights with actual outcomes
- Provide feedback (helpful/not helpful)
Acting on Insights
Review Carefully:
- Don't blindly follow AI recommendations
- Verify high-impact suggestions with experts
- Consider your specific context
- Use insights as starting point, not final answer
Prioritize Actions:
- Focus on HIGH risk factors first
- Implement quick wins immediately
- Plan for longer-term recommendations
- Delegate where appropriate
API Access
Generate Case Insights via API
curl -X POST https://api.torvussecurity.com/v1/ai/case-insights \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"caseId": "case_abc123",
"caseData": "Customer complaint about...",
"documents": ["doc_1", "doc_2", "doc_3"]
}'
Response:
{
"keyIssues": [
"Account access locked",
"Password reset failures",
"Customer frustration (3rd contact)"
],
"themes": ["account security", "technical support", "escalation"],
"actionableInsights": [
"Escalate to Tier 2 immediately",
"Manual account unlock required",
"Offer service credit for inconvenience"
],
"risks": [
{
"factor": "Customer churn risk",
"severity": "HIGH",
"description": "Frustrated customer, 3rd contact attempt"
}
],
"recommendations": [
{
"priority": 1,
"action": "Escalate to Tier 2 support",
"rationale": "Issue requires manual intervention"
}
],
"confidence": 0.87
}
for full documentation.
FAQ
How accurate are case insights?
80-90% accuracy for identifying key issues and themes. Recommendations should always be reviewed by humans before acting.
Can AI predict case outcomes?
No. AI can identify patterns from similar cases but cannot predict outcomes. Use insights to inform decisions, not make them.
Does AI learn from my cases?
Yes (optionally). AI learns patterns across your cases to improve recommendations. This is enabled by default but can be disabled in Settings → Privacy → Case Learning.
How does AI protect sensitive information?
All case data is encrypted before AI processing. AI provider (Google Gemini) does not retain your data.
Can I customize AI insight categories?
Not yet. AI uses predefined categories (key issues, risks, recommendations). Coming Soon: Custom categories for Enterprise customers.
How often should I regenerate insights?
After major updates: New documents, significant events, status changes Regular review: Weekly for active cases, monthly for monitoring cases
Getting Help
Support:
- Case Insights Issues: ai-support@torvussecurity.com
- Feature Requests: feature-requests@torvussecurity.com
Resources:
Last Updated: October 15, 2025