CONVENTIONALSTATE INTERRUPTED
Single-study execution
Configure one scenarioExecute an isolated runExport for offline analysisRebuild and repeat
RUNTIME SIMULATION ARCHITECTURE
One persistent runtime. Many live studies.
Train, engineer, and support operations from the same deterministic world state—without rebuilding the simulation between questions.
MULTI-INSTANCE EXECUTION FABRICRUNTIME ACTIVE
AUTHORITATIVE FOUNDATIONRuntimePhysics™World state · Physics · Time · CausalityPERSISTENT
BRANCH
01 / TRAINTraining instanceCompetency · Procedures · Teams
02 / ENGINEEREngineering instanceDesign · Compare · Validate
03 / OPERATEOperations instanceForecast · Advise · Integrate
LIVE INPUTS INInstances branch from one runtime foundation. No duplication. No drift.SIGNALS OUT
ContinuousState advances between questions, users, and operating horizons.
ConcurrentMultiple studies execute in parallel without rebuilding the world.
DeterministicIdentical inputs produce repeatable, auditable physical outcomes.
100 devicesUsers and systems interact with one synchronized runtime state.
WHY ARCHITECTURE MATTERS
Most simulation systems schedule jobs. Endeavor sustains a world.
The difference is structural. A job-based platform resets context between studies. A runtime-native platform preserves state, accepts change, and keeps executing.
RUNTIME-NATIVESTATE PERSISTS
Continuous execution
Execute liveBranch studies instantlyModify conditions during executionEvaluate inside the same environment
THE EXECUTION MODEL
One timeline governs every connected instance.
04Connected instances
03Execution fabric
02Persistent physics state
01Live system inputs
Scenarios are forked from the same runtime foundation, preserving deterministic physics while allowing conditions, parameters, and operator behavior to vary.
Training, engineering, and operational what-if analysis can coexist without duplicating the core system or reconciling results after execution.
Explore RuntimePhysics™ ↗CORE ARCHITECTURAL PILLARS
Capability built into the runtime—not assembled around it.
Multi-instance execution
Run multiple scenarios concurrently from a shared runtime. Studies branch instead of restarting the system.
Parallel what-if analysisInstructor-led branchingFaster iteration
Deterministic physics
Maintain a consistent ground truth across runs, assessments, connected systems, and safety-critical workflows.
Comparable outcomesAuditabilityStandardized evaluation
Real-time data integration
Ingest live PLC, sensor, control, and operational inputs while returning computed or synthetic signals.
Digital twin alignmentHardware-in-the-loopSynthetic data
Multi-user orchestration
Connect instructors, trainees, engineers, supervisors, observers, and external systems to one synchronized state.
Team-based trainingConcurrent rolesLive instructor control
STRUCTURAL EFFICIENCY
Branch studies. Not systems.
01Change conditions without resetting the world.
∞Explore alternatives from the same authoritative foundation.
ARCHITECTURE-DRIVEN APPLICATIONS
New workflows emerge without rewriting the core.
Adaptive training
Branch live scenarios while preserving repeatable assessment and crew context.
Engineering studies
Execute condition variations in parallel without reconfiguring the environment.
Operational twins
Align live field data with a continuously advancing physics state.
Hardware-in-the-loop
Put external controls and automation against deterministic live physics.
Synthetic data
Generate controlled outputs for analytics, assurance, and AI workflows.
RESEARCH FOUNDATIONS
The research behind persistent execution.
01 / MULTI-STUDY
Concurrent runtime execution
How independent studies run simultaneously while preserving timing, causality, and state integrity.
Explore research ↗02 / LIVE CHANGEEditing during execution
How active simulations accept new conditions without restarting, rebuilding, or breaking continuity.
Explore research ↗