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SIMUL

THE AI EXECUTION NETWORK

Intelligence, intelligently executed.

SIMUL coordinates AI workloads across models, providers, and compute infrastructure through one adaptive execution layer.

NETWORK
ONLINE
EXECUTION LAYER
ACTIVE
PROVIDERS
CONNECTED
ROUTING ENGINE
READY
EXECUTION ROUTING — LIVE SIMULATIONPACKET FLOW ACTIVE
APPLICATIONINPUTSIMUL EXECUTION COREMODEL 01MODEL 02INFERENCE NODESPECIALIZED SYSTEMCOMPUTE CLUSTER
SYS.04WHY SIMUL

AI infrastructure is fragmented. Execution shouldn't be.

SIMUL
EXECUTION LAYER
AI MODELS
INFERENCE PROVIDERS
COMPUTE ENVIRONMENTS
DOMAIN-SPECIFIC SYSTEMS
HIGH-CONTEXT SYSTEMS
SPECIALIZED AI INFRASTRUCTURE

Developers should not have to continuously integrate, monitor, compare and optimize every infrastructure provider independently.

SYS.02EXECUTION TERMINAL

Give SIMUL the mission. SIMUL finds the execution path.

PRIORITY50%
COSTQUALITY
LATENCY REQUIREMENT60%
RELAXEDREAL-TIME
CONTEXT REQUIREMENT40%
SMALLLARGE
RELIABILITY REQUIREMENT70%
STANDARDCRITICAL
EXECUTION ANALYSISSIMULATED EXECUTION DATA

CONFIGURE WORKLOAD PARAMETERS AND RUN ANALYSIS TO EVALUATE EXECUTION PATHS

SYS.03CORE EXECUTION FLOW

Five subsystems. One continuous mission.

01

WORKLOAD

Request received.

02

ANALYSIS

Requirements evaluated.

03

EXECUTION

Provider selected.

04

SETTLEMENT

Network activity recorded.

05

PERFORMANCE

Execution data contributes to future decisions.

SYS.05DYNAMIC EXECUTION

Different workloads require different infrastructure.

ROUTE ILLUMINATION — LOW-COST CLASSIFICATIONSIMULATED
APPLICATIONINPUTSIMUL EXECUTION COREMODEL 01MODEL 02INFERENCE NODESPECIALIZED SYSTEMCOMPUTE CLUSTER
SYS.06AI INFRASTRUCTURE MARKETPLACE

Infrastructure competes through execution.

PROVIDER RADARSIMULATED / DEMO DATA
SIMULGLM 5.3 FLASHFRONTIER MODEL 01EDGE INFERENCE GRIDCOMPUTE CLUSTER K7LONG-CONTEXT ARRAYVISION SPECIALIST X
AI MODEL

GLM 5.3 Flash

LATENCY
118 ms
PRICE
94/100
CAPACITY
92%
RELIABILITY
99.1%
AVAILABILITY
99.4%
CAPABILITY
84/100
HISTORICAL PERFORMANCE: EXCELLENT — DEMO DATA
SYS.07PERFORMANCE & REPUTATION

Performance becomes measurable.

COCKPIT ANALYTICSSIMULATED NETWORK TELEMETRY
SUCCESSFUL EXECUTION RATE
99.2%
AVERAGE LATENCY
186 ms
AVAILABILITY
98.6%
ERROR FREQUENCY
0.8%
EXECUTION COST
0.42 u
CAPACITY
63%
WORKLOAD-SPECIFIC PERFORMANCE — RECENT EXECUTIONS
EXECUTION IDTASKENVIRONMENTDURATIONSTATUS
SIM-897234autonomous_researchLong-Context Array431 msCOMPLETED
SIM-897233realtime_agentEdge Inference Grid96 msCOMPLETED
SIM-897232classify_100kGLM 5.3 Flash122 msCOMPLETED
SIM-897231image_understandingVision Specialist X254 msRETRIED
SIM-897230code_generationFrontier Model 01318 msCOMPLETED
NETWORK PREVIEW / SIMULATED DATA
SYS.08TRANSPARENCY DASHBOARD

Demand meets execution capacity.

NETWORK PREVIEW / SIMULATED DATA
EXECUTION VOLUME
1,284,317
NETWORK ACTIVITY
87%
INFRASTRUCTURE PARTICIPATION
214 nodes
EXECUTION PERFORMANCE
99.2%
PROVIDER AVAILABILITY
98.6%
SETTLEMENT ACTIVITY
41,208
NETWORK UTILIZATION
63%

Live network APIs are not yet provided. This board is architected so simulated feeds can be replaced by production telemetry without changing the interface.

SYS.09EXECUTION SETTLEMENT

Every execution can become a measurable network event.

Execution records are designed to capture what ran, where it ran, what it consumed, and how it performed — forming the settlement substrate of the network as the architecture matures.

SETTLEMENT MONITOR — STANDBY
BLOCKCHAIN-STYLE RECORDDEMONSTRATION DATA
EXECUTION IDSIM-897234
WORKLOAD STATUSCOMPLETED
EXECUTION ENVIRONMENTNODE-17
RESOURCE USAGE2.84 units
NETWORK FEE
PERFORMANCESUCCESS
SYS.10SIX-LAYER ARCHITECTURE

The SIMUL architecture, exploded.

01
REQUEST LAYER

Applications submit workloads and execution requirements.

02
ANALYSIS LAYER

SIMUL evaluates workload requirements and available execution conditions.

03
EXECUTION LAYER

Selected infrastructure processes the workload.

04
SETTLEMENT LAYER

Execution activity and associated costs are recorded and settled.

05
PERFORMANCE LAYER

Execution results contribute to infrastructure performance data.

06
PROVIDER LAYER

Infrastructure providers supply competing execution capacity.

Drag the hologram to rotate. Hover a layer to expand its role in the execution pipeline.

SYS.11AUTONOMOUS AGENTS

Agents decide what needs to happen. SIMUL coordinates how it happens.

AI AGENT
SIMUL
AI INFRASTRUCTURE
SEARCHREASONCODEANALYZESUMMARIZECALCULATEDECIDEINTERACT

Each generated workload carries its own requirements — SIMUL routes them toward different infrastructure dynamically.

SYS.12DEVELOPERS

One execution layer. Many AI environments.

EXECUTION REQUEST — CONCEPTUAL
{
  "task": "autonomous_research",
  "budget": "optimized",
  "latency_target": "standard",
  "quality_preference": "high",
  "context_requirements": "large"
}
SIMUL ANALYSIS
Workload classified
Requirements evaluated
Providers ranked
Execution path selected
Workload dispatched
BUILT FOR
AI AssistantsAutonomous AgentsSaaS PlatformsResearch SystemsData ProcessingDeveloper ToolsWorkflow AutomationConsumer AIAnalytics SystemsAlgorithmic Applications
SYS.13NETWORK INCENTIVES

Demand meets execution capacity.

APPLICATIONS

generate execution demand.

INFRASTRUCTURE PROVIDERS

supply execution capacity.

NETWORK PARTICIPANTS

support the broader ecosystem.

POTENTIAL INCENTIVES CAN ENCOURAGE
Reliable infrastructureUseful execution capacityDeveloper adoptionNetwork activityProvider participationEcosystem development
SYS.14$SIMUL — ROBINHOOD CHAIN

The coordination asset of the execution network.

$SIMUL token
$SIMUL
ROBINHOOD CHAIN

NETWORK EXECUTION

Used within the network execution and settlement architecture.

NETWORK FEES

Certain network operations may utilize $SIMUL for fee settlement.

PROVIDER PARTICIPATION

Providers may interact with token-based participation mechanisms.

ECOSYSTEM INCENTIVES

Can support incentives encouraging useful network activity and infrastructure participation.

GOVERNANCE

May enable community participation in selected network parameters where governance systems are implemented.

Token functionality may evolve alongside the network.

AI will not be defined by a single model.

It will be defined by how intelligently AI infrastructure is coordinated.

SIMUL
INTELLIGENCE, INTELLIGENTLY EXECUTED.