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Enterprise Layer Intelligence
Categories/Data Analytics/Rocketgraph
Rocketgraph

Rocketgraph

Founded 2014

Analyze massive graph datasets to detect fraud, money laundering, and cybersecurity vulnerabilities

Pricing model

Demo

You can use Rocketgraph to inspect massive graph datasets with hundreds of billions of nodes and edges at high speeds. The system lets analysts query deep connection layers across complex data networks to uncover hidden relationships. Teams use it to spot fraud networks, identify money laundering pathways, and prioritize software vulnerabilities by tracing live exploit exposure. Built-in generative AI models connect directly to your graph data to accelerate investigations. It runs deep multi-layer queries without crashing systems or requiring extra database upkeep.

What Rocketgraph does

Map entity relationships across disparate databasesScan graph networks dozens of layers deepTrace circular transaction paths in financial dataPrioritize known exploited vulnerabilities by asset impactDetect anomalous transaction clusters across customer accountsQuery graph databases using connected language modelsIn-memory graph processing capable of handling hundreds of billions of nodes and edgesDeep graph traversal scanning dozens of connection layers deepIntegration with private and public large language models for graph explorationEntity resolution linking customers, devices, merchants, and transactionsContinuous link analysis to detect circular money flows and money mule clustersVulnerability prioritization mapping asset software bills of materials directly to known exploits

Pricing breakdown

Pricing model: Book a demo

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Rocketgraph, graph analytics, graph database, fraud detection, anti-money laundering, vulnerability management, attack surface management, xGT, cyber threat intelligence, link analysis, big data analysis, entity resolution, KEV prioritization, knowledge graph, cyber security analytics