Advanced intrusion detection with real-time aggregation, anomaly spotting, and intelligent blocking policies
Instant threat detection and response with millisecond latency
Machine learning algorithms detect anomalies with precision
Intelligent policies automatically neutralize threats
Enterprise-grade security features designed for modern streaming architectures
Collect and process data from multiple sources in real-time with high-throughput pipelines
Advanced ML models identify unusual patterns and potential threats before they escalate
Automated response policies block malicious activity with configurable rules and thresholds
Sub-millisecond processing ensures minimal impact on stream performance and user experience
Comprehensive visualizations and insights into your security posture and threat landscape
Horizontally scalable infrastructure handles millions of events per second effortlessly
A seamless three-step process to secure your streaming infrastructure
Connect your data sources and start streaming events through our high-performance ingestion layer. Support for Kafka, WebSockets, HTTP, and custom protocols.
AI models process events in real-time, identifying patterns, anomalies, and potential threats. Advanced correlation engines detect sophisticated attack vectors.
Automatically enforce policies to block malicious actors while alerting your team through multiple channels. Full audit trail for compliance.
StreamGuard AI leverages cutting-edge technologies to deliver unparalleled performance and reliability in stream security.
Apache Kafka and Flink for fault-tolerant stream processing
TensorFlow and PyTorch models for anomaly detection
Kubernetes orchestration with auto-scaling capabilities
Uptime SLA
Avg Latency
Events/Sec
Monitoring
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