Enterprise Compute Layer

Deploy and scale AI workloads across your infrastructure. Full control, zero lock-in, compliance by design.

1. Distributed Compute Architecture
How your AI workloads are distributed across regions for maximum resilience and compliance.
Global Compute Distribution EU Data Center GDPR-compliant AI Model Inference Local Processing Zero egress option US Data Center High-performance GPU Training & fine-tuning Cloud provider optional Scalable resources APAC Data Center Low-latency serving Regional cache Load balancing Disaster recovery Orchestration & Routing Layer Workload distribution • Compliance zoning • Auto-failover Data residency enforcement • Cost optimization
2. Scalable GPU Cluster Architecture
How compute nodes are organized for efficient training and inference workloads.
GPU Cluster Organization Cluster Controller Job scheduling & resource mgmt GPU Pool A GPU 1-4 GPU 5-8 Memory Pool Network GPU Pool B GPU 1-4 GPU 5-8 Memory Pool Network GPU Pool C GPU 1-4 GPU 5-8 Memory Pool Network
3. Workload Distribution by Type
Different workloads are automatically routed to optimal compute resources.
Intelligent Workload Routing Real-time Inference • Voice synthesis • Instant responses • <500ms latency • Edge/local GPU Batch Processing • Document analysis • Bulk transformations • Hours/days timeline • Cost-optimized GPU Model Training • Fine-tuning • Full pipeline training • Multi-day runs • Max GPU resources Intelligent Orchestrator Analyzes workload characteristics • Auto-selects optimal resource pool Enforces compliance zone routing • Monitors costs & performance Handles scaling • Manages job queues • Provides feedback
4. Enterprise Compute Deployment Options
Choose the deployment model that fits your infrastructure and compliance needs.
Deployment Models On-Premise Your own hardware ✓ Full data control ✓ Zero cloud egress ✓ CONFIDENTIAL data ✓ Hermes local AI EU-Cloud Hosting EU data centers only ✓ GDPR compliant ✓ No US egress ✓ Art. 44 compliant ✓ Managed by us Hybrid Compute Local + cloud blend ✓ Best of both ✓ Cost optimized ✓ Flexible routing ✓ Failover ready

Enterprise-Grade Compute Capabilities

CorvinOS Compute Layer gives you enterprise-grade AI inference, training, and batch processing with complete control over where your data goes and where computation happens.

🚀 Auto-Scaling

Automatically scale GPU resources based on workload demand. Pay only for what you use, with intelligent resource pooling.

🔒 Compliance Zones

Define compute resources per compliance zone. EU workloads on EU GPUs, CONFIDENTIAL data on-premise only.

⚡ Multi-Engine

Switch between Claude, local Hermes, and other models without changing your workload code. Optimize cost and latency.

📊 Monitoring & Logging

Full observability into compute job execution, performance metrics, and cost tracking. Audit trails for every job.

🔄 Failover & HA

Automatic failover between GPU pools and regions. 99.9% SLA for critical workloads. Zero downtime updates.

🛠️ Custom Integration

Integrate your existing CI/CD pipelines. Custom scheduling, resource reservations, and priority queues.

Real-World Enterprise Use Cases

Financial Services

Process millions of loan applications, compliance documents, and regulatory filings. Keep all data on-premise with zero cloud egress.

Healthcare & Life Sciences

Analyze patient data, medical imaging, and clinical research. EU-only deployment for GDPR and medical device compliance (MDR/IVDR).

Government & Defense

Classified workloads on secured infrastructure. Custom compliance zones, audit trails, and air-gapped deployments.

Legal & Compliance

Analyze contracts, discovery documents, and regulatory submissions. Full audit trails for eDiscovery and litigation support.

Ready to Deploy?

Discuss your compute requirements with our enterprise team. We'll design a solution for your data residency and compliance needs.

Get Started on GitHub