Enterprise-grade infrastructure engineered for cross-divisional scale. Unified compute, data lakes, AI pipelines, and global edge networking under a single control plane.
Modular services designed to scale independently while maintaining seamless cross-divisional data synchronization.
GPU/CPU hybrid orchestration with auto-scaling node clusters. Optimized for high-frequency trading, telemetry processing, and ML training workloads.
Petabyte-scale object storage with tiered archival. Real-time stream processing via Q-Stream pipelines with schema enforcement.
End-to-end model lifecycle management. Distributed training, vector database integration, and low-latency inference endpoints.
Hardware-backed encryption, identity-aware proxy, and continuous compliance scanning. FIPS 140-3 validated modules.
Infrastructure as code, one-click provisioning, and native SDKs for every major language.
| Parameter | Specification | Compliance |
|---|---|---|
| Storage IOPS | Up to 1.2M / volume | SOC 2 Type II |
| Network Throughput | 200 Gbps / vNIC | HIPAA Ready |
| Encryption | AES-256-GCM / TLS 1.3 | FedRAMP High |
| Backup RPO/RTO | RPO: 5 min | RTO: 2 min | ISO 27001 |
| Edge Nodes | 380+ POPs globally | GDPR Compliant |
Q-Cloud powers internal Aevum Zenth operations while offering secure, isolated tenant environments for partners.
Real-time orbital data ingestion & trajectory simulation at 10kHz.
HIPAA-compliant genomic data lakes & federated learning pipelines.
Sub-millisecond market data feeds & risk modeling clusters.
Smart meter aggregation, predictive load balancing & fault detection.
Digital twin simulation & edge inference for autonomous fleets.
IoT freight tracking, route optimization & customs compliance APIs.
Custom SLAs, dedicated support engineers, and private vCloud deployments available for enterprise contracts.