Hybrid Infrastructure
Deploy EmberGrid across cloud, edge, and private clusters with unified control.
The Control Plane for ModernAI Infrastructure
Unified orchestration for GPU clusters, model deployment, and distributed AI workloads across modern enterprise environments.
Trusted by category-defining teams
CAPABILITIES
GPU ORCHESTRATION.png)
WORKLOAD SCHEDULING
HYBRID DEPLOYMENT
OBSERVABILITY
CAPACITY PLANNING
AI INFRASTRUCTURE.MEASURABLE PERFORMANCE.
EmberGrid helps enterprise teams deploy, monitor, and optimize AI infrastructure across GPU clusters, cloud regions, and edge environments with precision and control.
PERFORMANCE
FOUNDATION
ENGINEERED BY EXPERTS.
BUILT FOR SCALE.
With a strong foundation in AI infrastructure and distributed computing, we combine engineering expertise and enterprise strategy to power every deployment.
INFRASTRUCTURE FOUNDATION
V2 GRID ARCHITECTURE
Introduced unified compute management
GPU orchestration,
workload management, and deployment automation.
FLAGSHIPCompute Orchestrator
Unifies GPU pools, model runtimes, and distributed workloads through one intelligent control plane designed for enterprise AI operations.
Workload scheduling
Allocate compute across clusters with policy-driven efficiency.
Infrastructure observability
Monitor utilization, health, and throughput in real time.
Deployment automation
Launch models, roll back safely, and connect inference pipelines without manual handoffs.
Cloud & edge integration
Built for hybrid scale
Deploy EmberGrid across your private cloud, edge sites, and distributed clusters with a single operating layer.
Capacity intelligence
Forecast demand and optimize compute spend before bottlenecks hit.
Why AI teams
Choose EmberGrid
EmberGrid was built to give modern enterprises a dependable path to AI infrastructure scale without sacrificing observability, efficiency, or control.
Compute Intelligence
Optimize with intelligent resource allocation and accelerated infrastructure performance.
Enterprise Security
Deploy AI infrastructure across secure, private, and controlled environments.
Workload Orchestration
Manage distributed AI workloads across clusters with automated coordination.
Cost Optimization
Improve infrastructure efficiency through smarter compute utilization.
Six products.
One coherent platform.
Compute Orchestrator
Coordinate GPU pools, inference servers, and distributed workloads through one control plane.
Workload Scheduler
Place AI jobs intelligently across cloud, edge, and on-prem clusters.
Model Deployment
Automate model rollout, versioning, rollback, and inference lifecycle management.
Observability Layer
Track utilization, cluster health, latency, and cost optimization in real time.
Capacity Intelligence
Forecast demand and rebalance resources before performance bottlenecks emerge.
Hybrid Integrations
Connect Kubernetes, cloud providers, APIs, and private infrastructure in one workflow.
Wherever AI workloads live,
EmberGrid moves.
GPU cluster orchestration
Balance distributed compute capacity across on-prem and cloud infrastructure.
Inference scaling
Scale model serving dynamically as demand fluctuates across regions.
Model deployment pipelines
Automate release, rollback, and version control for enterprise AI services.
Edge AI operations
Run local workloads with centralized coordination and observability.
Resource optimization
Reduce waste and improve utilization across shared infrastructure fleets.
Cost-aware planning
Forecast compute demand and align investment with actual workload patterns.
Platform monitoring
Surface anomalies, latency issues, and operational risk before they impact production.
Hybrid readiness
Coordinate cloud-native and private environments through one operational layer.
An infrastructure layer,
built for AI operations.
GPU orchestration
Balance clusters and allocate compute intelligently
Workload scheduling
Route jobs across cloud, edge, and private environments
Model deployment
Manage releases, rollout policies, and rollback workflows
Capacity planning
Forecast demand and optimize spend before bottlenecks
Observability
Track latency, health, utilization, and throughput
Hybrid integration
Connect APIs, Kubernetes, and distributed infrastructure
GPU orchestration
GPU orchestration
Balance clusters and allocate compute intelligently
Workload scheduling
Workload scheduling
Route jobs across cloud, edge, and private environments
Model deployment
Model deployment
Manage releases, rollout policies, and rollback workflows
Capacity planning
Capacity planning
Forecast demand and optimize spend before bottlenecks
Observability
Observability
Track latency, health, utilization, and throughput
Hybrid integration
Hybrid integration
Connect APIs, Kubernetes, and distributed infrastructure
Five layers.
One operating system for AI infrastructure.
Experience layer
APIs · Dashboards · Control surfaces
Orchestration layer
Scheduling · Routing · Policy enforcement
Compute layer
GPU clusters · Inference pools · Workloads
Data layer
Model artifacts · Metrics · Telemetry
Runtime layer
Cloud · Edge · Private infrastructure
Every workload,
rendered in real time.
GPU utilization
84%
+6%
Active workloads
3,218
+124
Inference latency
38ms
-6ms
Cluster health
99.98%
+0.2
Compute throughput
LIVEMix
Regional performance
Notifications
Agent-4 deployed
2m ago
Policy update accepted
12m ago
APAC region scaled +18%
1h ago
New integration: SAP S/4
3h ago
From integration
to steady operations.
Assess
We audit your compute landscape, workload patterns, and deployment goals to map the right infrastructure path.
Integrate
We connect your clusters, cloud platforms, APIs, and deployment pipelines into EmberGrid's control layer.
Deploy
Launch models and workloads into production with rollout controls, observability, and rapid rollback.
Observe
Track utilization, latency, and health in real time so your operations stay reliable and cost-aware.
Scale
Expand across regions, environments, and new model workloads without losing operational visibility.
Numbers infrastructure teams trust.
PRICE LIST COLLECTION
For teams launching their first GPU-backed workloads.
For organizations running distributed AI operations at enterprise scale.
Air-gapped, regulated, and mission-critical infrastructure deployments.
The teams building the
next decade, on EmberGrid.
"EmberGrid reduced our GPU coordination effort from days to minutes."
Isabelle Moreau
Chief Risk Officer, Meridian Bank
"The only infrastructure platform our security team approved without redlines."
Kenji Watanabe
CISO, Volta Aerospace
"It feels less like software and more like an operating layer for AI."
Priya Rao
VP Operations, Halcyon Health
"We moved from manual model deployment to automated production workflows in under three weeks."
Marcus Bell
Head of Platform, Nexus Trading
"The observability and scheduling views alone justified the rollout."
Sofia Alarcón
COO, Arcadia Retail
"EmberGrid scales dynamically without friction, allowing our researchers to focus purely on algorithms."
David Chen
Head of AI, Vanguard Tech
We Deliver
Enterprise AI Infrastructure
EmberGrid specializes in delivering tailored enterprise infrastructure solutions for GPU orchestration, workload scheduling, deployment automation, and real-time observability across cloud, edge, and hybrid environments.
Get StartedCustom Agent
Architecture
Tailored software solutions designed to fit your specific business logic needs, ensuring seamless integration and optimal performance.
Including With:
- Autonomous Decisioning
- Real-time Policy Enforcement
- Continuous Evaluation Loops