In the race to deliver business value with AI, shortcuts are tempting. Why can Rapid7 resist? We began our AI 和 machine learning journey decades ago. Our approach remains thoughtful, 测量, 和 protective of data privacy 和 our own security st和ards. Data-centric AI has been (quietly) embedded in our platform for years, powering risk 和 threat analysis, detecting attacks earlier, reducing response time. 现在, we’ve added a generative AI engine trained on proprietary data 和 trillions of security events we observe weekly.
Rapid7’s AI-powered platform detects threats as they happen across your environment, automatically validating if the activity is malicious, so you have the clarity 和 confidence to act.
AI sees subtle patterns 和 anomalies that a human eye cannot. It suppresses benign alerts, organizes priorities, 和 guides your team to what matters – all integrated into workflows.
Breaches are “inevitable” now, so be proactive, control exposures, 和 use AI integrations. Even short-staffed programs with novices 和 budget pressures can excel.
现在, Rapid7 supercharges SecOps in partnership with AWS. Our MDR SOC can help customers rapidly identify critical anomalies 和 recognize threats evolving in real time. 在本指南中, 由AWS共同撰写, you’ll learn how the Rapid7 人工智能引擎 enables intelligent threat detection, secure AI/ML application development, 和更多的.
Rapid7’s Pojan Shahrivar 和 Dr. Stuart Millar developed AI 和 ML techniques that effectively prevent 94% of brute-force DAST attacks, 和 eliminate the entire kill-chain at the source.
的成就? The use of AI/ML to triage vulnerability remediation, reducing false positives by 96%. Our team took this coveted award ahead of the likes of Apple 和 Microsoft.
We’ve had a specialist data presence in Belfast for years. Today, it’s our largest R&D hub outside the US. At the core of our AI engineering is a data-centric approach