Arrcus targets AI inference bottleneck with policy-aware network fabric
As AI workloads shift from centralized training to distributed inference, the network faces new demands around latency requirements, data sovereignty boundaries, model preferences, and power constraints.
By Sean Michael Kerner
Feb 20, 2026 5 mins
Artificial IntelligenceNetwork Management SoftwareNetworking