Rapid7's Vice President of Data and AI Laura Ellis shares how they built an AI-first cybersecurity platform by investing in AI platform AND data infrastructure simultaneously.

Topics Include:

Rapid7 processes massive cybersecurity data across exposure management, threat detection, and managed SOC.
84% of security analysts want to quit due to data overload burnout.
Challenge: investing in AI platform AND data infrastructure simultaneously, not sequentially.
Built security data lake with AWS, unified IDs, and standardized schemas across products.
Used traditional machine learning for 10 years before generative AI emerged.
Generative AI raised questions about business impact; agentic AI enables full automation.
Chose AWS for scale, model marketplace flexibility, and true partnership on capacity.
Co-development incubator with SOC team proved critical: equal responsibility, full-time collaboration.
Launched alert triage automation, SOC assistant chatbot, and incident report generation tools.
Built AI platform with guardrails after pen testers generated cookie recipes costing money.
One agentic feature initially cost-estimated at $140 million before optimization and guidance.
Future: more AI features, granular customer configuration, and bring-your-own-model capabilities.

Participants:

Laura Ellis – Vice President, Data & AI, Software Engineering, Rapid7

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