Cerebellum
GPU-accelerated AI platform that receives metadata from all deployed Cerebrum sensors. Cross-site correlation, encrypted traffic classification, and continuous learning — the brain behind every sensor.
Real-time threat classification powered by NVIDIA Grace Hopper. 528 Tensor Cores with 900 GB/s memory bandwidth between CPU and GPU for inference at scale.
Classify threats inside TLS without decryption. Neural network models analyze connection metadata, packet sizes, timing patterns, and JA4+ fingerprints.
Detect lateral movement and coordinated attacks spanning multiple locations. Every sensor feeds into a unified threat graph that identifies multi-stage attack chains.
Learns your network's baseline and flags deviations in real time. Detects zero-day threats, insider attacks, and compromised credentials without signatures.
Pushes updated threat verdicts and detection models back to all deployed sensors automatically. Every sensor gets smarter as the network learns.
Run Cerebellum as a managed SaaS service or deploy on-premises for full data sovereignty. Same capabilities, your choice of deployment.
Built for Scale
Start with a single sensor at one location. Add more as you grow. Every sensor makes the AI smarter, and every AI insight makes every sensor more effective.