AI Case Solver
AI automatically analyzes collected information to connect related entities, summarize complex findings, detect hidden relationships, and organize case evidence into clear investigative paths.
Core AI Capabilities
Intelligent automation designed for modern cyber investigators and intelligence analysts.
Connect Related Entities
Link phone numbers, vehicles, email profiles, and physical addresses into a unified intelligence graph.
Summarize Findings
Instantly translate thousands of raw data points into actionable executive briefings.
Detect Relationships
Uncover hidden co-location occurrences, shared domain registrations, and cross-platform mentions.
Generate Investigation Reports
Auto-compile court and compliance-ready reports complete with timestamped citations.
Organize Evidence
Tag, categorize, and verify open-source artifacts with immutable chain-of-custody tracking.
Produce Structured Timelines
Chronologically map all discovered events, phone activity, and registry updates.
Investigation Workflow with AI
1. Input Artifacts
Provide initial investigative seeds: phone numbers, plate numbers, email handles, or suspicious transaction data.
2. Automated Correlation
The AI engine queries multi-source lawful registries, clusters overlapping entities, and isolates common threat patterns.
3. Actionable Briefing
Outputs comprehensive threat evaluations, confidence scores, and instant exportable PDF case dossiers.
Frequently Asked Questions
How does the AI Case Solver analyze OSINT data?
The AI Case Solver uses advanced natural language processing and graph neural reasoning to correlate disjoint data points—such as phone numbers, vehicle registrations, email addresses, and timestamps—into unified subject profiles.
Can the AI Case Solver generate legal and court-ready reports?
Yes. It automatically compiles comprehensive investigation briefs with structured executive summaries, entity relation graphs, timeline maps, and verified source citations exportable to PDF.
How does AI calculate entity confidence scores?
Confidence scores evaluate source provenance, cross-platform corroboration, and data freshness to assign an objective 0–100% confidence rating to every discovered artifact.