Skopenow
Analytical search engine for insurance claims fraud detection and due diligence
Overview
Skopenow is an open-source intelligence (OSINT) platform providing comprehensive online research and analytical tools for fraud detection and due diligence. The platform aggregates data from crime databases, public records, consumer information, news sources, media content, and online databases to deliver actionable intelligence to insurance carriers, law enforcement, legal professionals, and security organizations.
The company offers a cloud-based suite of products leveraging AI-powered models for fraud detection, risk assessment, and investigative research. Skopenow's API-first architecture enables integration with carrier workflows for automated risk signaling and real-time threat detection. The platform serves a diverse customer base including insurance carriers, law enforcement agencies, government entities, legal firms, private investigators, and media organizations.
Skopenow has established strong market traction with over 1,500 customers globally, including 20% of Fortune 500 companies. Venture-backed with Series A funding of USD 2.5M, the company continues to expand its position as a leading provider of OSINT capabilities for the insurance and investigative sectors.
Products & Services
Workbench
Comprehensive entity search and intelligence reporting tool for fraud investigation and underwriting due diligence. Generates detailed reports on individuals and organizations with connection mapping and risk assessment.
Key Features
- Entity and relationship searches across millions of public records
- Automated fraud and risk signal generation
- Connection mapping and network visualization
- Export capabilities for case management integration
Target Users: Claims investigators, underwriters, loss prevention specialists, legal due diligence teams
Link Analysis
Network visualization and relationship mapping tool for uncovering connections and patterns across entities. Enables rapid identification of suspicious networks and fraud rings.
Key Features
- Real-time relationship mapping and visualization
- Multi-hop connection analysis
- Risk pattern identification
- Automated network scoring
Target Users: Claims fraud investigators, law enforcement, intelligence analysts
Grid
Real-time threat detection and situational awareness platform providing live data feeds and geospatial intelligence for active investigations.
Key Features
- Real-time data feeds and alerts
- Geospatial intelligence and location tracking
- Live threat dashboards
- Situational awareness reporting
Target Users: Law enforcement, government agencies, security operations centers
Pre-Check
Automated fraud and risk signaling system that flags potential risks and fraud indicators in real-time using public records and proprietary data sources.
Key Features
- Real-time risk scoring on new claims
- Automated fraud indicator detection
- Integration with claims intake systems
- Customizable risk thresholds and rules
Target Users: Claims departments, underwriting teams, carriers
Rabbit
Fast exploratory intelligence tool designed for rapid OSINT investigations and open-source information gathering on subjects of interest.
Key Features
- Quick subject searches and profile generation
- Fast data aggregation from multiple sources
- Lightweight investigation tool
- Rapid report generation
Target Users: Investigative professionals, journalists, security researchers
At a Glance
- Founded
- 2016
- Headquarters
- New York, NY, USA
- Employees
- 51-200
- Funding
- Series A
Category & Focus
- Category
- Claims Technology
- Subcategories
- Fraud Detection Risk Scoring Due Diligence
- Insurance Verticals
- P&C Commercial P&C Personal Specialty/E&S
- Target Customers
- Carriers, Law Enforcement, Legal Professionals, Government Agencies, Loss Prevention
Customers
- 20% of Fortune 500 companies
- US law enforcement agencies
- Federal government agencies
- International government organizations
- Major insurance carriers
- Law firms
- Private investigation firms
- Media organizations
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Last updated: 2026-06-17