Defense in Depth How Can AI Provide Useful Guidance from Fragmented Security Data?
Jul 31, 2025
Matt Eberhart, CEO of Query AI, leads a Federated Search and Analytics platform that optimizes security data management. He discusses the crucial importance of data quality over sheer volume in AI-driven decision-making. The conversation touches on the connectivity challenges faced by security teams and highlights how graph-based models can enhance AI applications. Eberhart emphasizes the transformative potential of AI in reducing burdensome workflows, enabling analysts to focus on strategic insights instead of repetitive tasks.
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Fragmented Security Data Limits AI
- Security data is fragmented and siloed across many sources, hindering complete context.
- AI tools without full context can only see part of the picture, limiting their effectiveness.
Shift From Efficiency to Protection
- Seeing the right amount of trusted data quickly is essential for effective decisions.
- Shifting focus from SOC efficiency to overall company protection is crucial.
Prioritize Quality Over Quantity
- Focus on relevant, high-quality data tied to your threat model and risk appetite.
- Use only the data needed to make informed decisions rather than collecting everything.