


CortexOne™
Built for inference, agents, workflows, and large-scale batch execution.
Inputs
Models
Agents
Batch Jobs
CortexOne Routing Layer
Real-time evaluation & intelligent routing
Execution
CPU Pools
GPU Clusters
Accelerators
Speed
Real-time routing to the fastest hardware available.
Optimized inference paths
Sub-100ms execution
Security
Encrypted at the processor level.
Zero data retention
Fully isolated execution environments
Savings
30–60% lower compute cost through intelligent routing.
Per-second billing
Dynamic resource allocation
The Problem
AI performance breaks down at execution.
Most enterprise AI slowdowns come from how workloads are scheduled, routed, and
run.
Legacy Execution
Fixed Hardware
Static allocation regardless of workload
Queueing Delays
Jobs wait for designated resources
Idle Capacity
Provisioned but unused compute
Manual Routing
Teams manage infrastructure decisions
The Solution
An execution layer designed for real workloads.
CortexOne dynamically routes every task to optimal compute, eliminating bottlenecks.
CortexOne Execution
Dynamic Routing
Tasks matched to optimal hardware in real time
Parallel Execution
Workloads distributed across available capacity
Hardware Flexibility
Automatic adaptation to resource availability
Zero Manual Overhead
Platform handles orchestration decisions
01
/ 05
Detect
Identify workload type (LLM, vision, agent, batch job)
02
/ 05
Benchmark
Evaluate available clouds, GPUs, runtimes, and models
03
/ 05
Select optimal hardware path automatically
04
/ 05
Secure
Encrypt inputs at processor level and run in isolated containers
05
/ 05
Deliver
Return output with full telemetry, logging, and audit trail
Workload Input
Incoming Task
Inference request, agent call, or batch job
CortexOne Routing Engine
Evaluate
Route
Execute
Optimal Target
CPU Pool
GPU Cluster
Selected
Accelerator
Real-time workload routing
Tasks are matched dynamically to the hardware that finishes them fastest.
Hardware-agnostic execution
Run across CPUs, GPUs, and accelerators. NVIDIA, AMD, Intel, and custom hardware.
Consistent performance under load
Reduce queueing and variability as workloads scale.
Unified execution model
Use the same execution layer for inference, agents, and batch jobs.
Existing models and frameworks
Internal data pipelines
Enterprise orchestration tools
Rival Marketplace functions
No disruption to existing architecture
Applications / Models
Your Workloads
LLMs, ML Models, Agents, Pipelines
LLMs
ML Models
Agents
Pipelines
CortexOne
Intelligent Routing Layer
Route
Optimize
Monitor
Control Plane
Orchestration & Policy
Scheduling
Policies
Quotas
Execution Plane
Compute Resources
CPU
GPU
TPU
Custom
Financial Services
65%
Global financial services firm reduced a three-week content tagging bottleneck to hours by parallelizing execution across millions of documents.
View Case Study
Engineering and Platform Teams
Reduce operational overhead while maintaining performance guarantees.
Data and AI Teams
Run experiments and production workloads without infrastructure bottlenecks.
Technology Leadership
Gain cost visibility and predictable execution as AI usage grows.

Ready to Optimize?
30-60%
Cost Reduction
<100ms
Execution Time
Zero
Data Retention
100%
Hardware Agnostic
