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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