Investigative Analytics for Cyber, Fraud, & AML
Turn complex data into clarity through exploratory visual graph analytics & graph AI
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Modern investigations break when analysts are forced to guess the right query too early.
Cyber incidents, fraud rings, and money-laundering schemes don’t follow neat schemas - they emerge as networks of relationships over time. Graph analytics lets you see those relationships instantly, pivot in real time, and follow the evidence wherever it leads.
This masterclass shows how to engineer data for graph analytics and use interactive visual exploration to uncover threats, fraud, and hidden networks - faster and with more confidence.
Designed for teams who work with complex, high-volume data:
No prior graph experience required.
Data Engineers building pipelines for security, fraud, or compliance
Cybersecurity Analysts & SOC Teams investigating alerts and campaigns
Fraud & AML Investigators uncovering coordinated networks
Data Scientists & Analytics Leaders supporting investigative workflows
Model tabular data as investigation-ready graphs
Build scalable graph pipelines from SQL, logs, and transaction data
Use exploratory visual analytics to surface anomalies and hidden structures
Pivot through relationships without writing complex queries
Apply graph workflows to cybersecurity, fraud, and AML use cases
Move from ad-hoc exploration to repeatable investigative playbooks
Join our instructors with incident response scars and track records in AI+data technology breakthroughs
so you know what works today and what's coming next.
🏆🏆🏆
First agentic AI speedrun of Splunk Boss of the SOC CTF
"I went from AI zero… to AI hero!"
- Incident Response Lead
"The class summarize very well the AI state-of-the-art concepts while running hands-on labs."
- Andreas Rohr, founder & CTO, DCSO (MSSP)
Data Engineering for Graph Analytics
Learn how to transform logs, events, and transactions into graph-ready models that scale.
Exploratory Visual Analytics
See patterns emerge before you know what to ask - clusters, anomalies, hubs, and bridges.
Cybersecurity Investigations
Track lateral movement, credential abuse, and attack campaigns across infrastructure and identities.
Fraud & AML Investigations
Uncover hidden networks, synthetic identities, and money-laundering typologies.
From Insight to Action
Operationalize investigations, share findings, and integrate with SOC and compliance workflows.
Limited to 45 participants to keep sessions high-quality
Early Bird (2.5 Weeks)
Regular
Group Discount
15% off for 3-5 participants
Limited Availability
Capacity at 45 participants to ensure quality
🇺🇸 Americas Timezone - In Person
March 24, 2025
San Fransisco, CA - In Person
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Live instruction from graph analytics experts
Hands-on labs and investigation datasets
Reference data models for cyber, fraud, and AML
Investigative playbook templates
Certificate of completion
Instructors
Founder & CEO of Graphistry, co-creator of Louie.ai
Pioneer in GPU-accelerated visual graph intelligence. Leo helped launch open-source ecosystems like Apache Arrow and NVIDIA RAPIDS, and holds a PhD in Computer Science from UC Berkeley. Leo led the first successful agentic AI speed-run of Splunk Boss of the SOC (BOTS), and his team won the U.S. Cyber Command AI RPE competition for alert volume reduction. He works closely with global government agencies, major enterprises, financial institutions, and technology companies on data-intensive investigation technologies across cybersecurity, fraud, and national intelligence. Earlier, he contributed to R&D efforts at Microsoft and Adobe, where he recieved the SIGPLAN 10yr Test of Time award and multiple Best Paper awards.
Solutions Architect at Graphistry
Former Chief Inspector at Kripos (Norwegian National Criminal Investigation Service) and senior analyst at Defendable MSSP. Sindre is an expert in SOC automation, security graph intelligence, and GenAI for investigations, and advises banks, government agencies, tech companies, and various enterprises in their deployments.
Visualization Engineer
Manfred is a visualization engineer at Graphistry with a deep background in graph visualization rendering and experience in visualization design. Previously he was one of the core maintainers of CytoscapeJS - a leading graph visualization library, and of Grafer - a high performance GL visualization library. He co-authored the "Best Paper" at the IEEE VIS 2021 conference for graph approaches to large-scale biomedical knowledge exploration.
Director of Technical Sales at Graphistry
Thomas Cook is Director of Technical Sales at Graphistry, where he helps organizations apply GPU-accelerated graph analytics to investigations, fraud detection, cybersecurity, and large-scale data exploration. He works closely with engineering and analytics teams to operationalize visual graph analytics, property-graph querying, and AI-assisted workflows directly on Arrow- and Parquet-based data—without requiring storage migration or specialized graph infrastructure.
Senior practitioners with backgrounds across enterprise SOCs, MSSPs, SIEMs, government agencies, and developers of various AI and high-performance computing technologies.