Traditional SIEMs Can't Support AI
Traditional SIEMs can't handle AI workloads. Queries are too slow and too expensive for agents to explore freely.
Scanner is the only security data lake with the speed and economics to make AI-driven security actually viable.
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"We can search through a full year of logs in seconds, giving us visibility into an order of magnitude more data than before. Analysis at this kind of scale is essential in the cloud era."
- Jonathan Jaffe, CISO | Lemonade
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Why Traditional SIEMs Can't Support AI
AI agents need to iterate, explore, and query freely. Traditional systems are too slow and too expensive for this.
Too Slow For AI Iteration
AI agents need to run dozens of exploratory queries to understand data and find threats. When each query takes 30 minutes, AI investigations timeout or become impractical.
Scanner's sub-second queries let AI agents iterate freely, running 20+ queries in the time traditional systems complete one.
Too Expensive for AI Workloads
AI agents don't know which queries will be useful until they run them. Traditional systems charge $50-100 per query, making AI exploration prohibitively expensive.
Scanner's query costs ($0.01-0.10) make it economically viable for AI to explore freely without budget constraints.
Traditional SIEMs Break at Cloud Scale
Modern cloud infrastructure generates more data than legacy tools can handle. The result:
Your Queries Get Slower
As your data grows, query times balloon from seconds to minutes - and then to hours. When every second counts during an incident, waiting isn't an option.
You're Forced to Drop Data
Retention windows shrink to days or weeks. Logs get sampled. The choice between visibility and cost creates blind spots attackers exploit.
Your AI Tools Can't Run
AI needs complete historical context to work effectively. Slow queries and limited retention mean your security copilots sit idle or timeout.