A precise, operational definition of a digital twin grounded in continuous runtime execution.
A digital twin is a continuously authoritative representation of a physical system as it operates in real time. Endeavor’s digital twin architecture maintains system state, timing, and causality within a single unified runtime engine. This architecture recomputes physics and operational logic as inputs evolve, enabling consistent decision outcomes without reliance on staged runs, scripted scenarios, or post-hoc reconciliation.
The defining attribute of a digital twin is its ability to maintain authoritative state across all relevant subsystems. At run time, physics, temporal evolution, and operational decisions are resolved within the same system that owns the state. Unlike systems that replay historical data or stitch together discrete executions, a true digital twin continuously evolves with live inputs, preserving determinism and historical continuity.
In Endeavor’s implementation, continuous recomputation allows decision impacts to be observed in context. Inputs such as sensor streams, control setpoints, and environmental data are absorbed into an active state model. Outcomes are produced by the same execution loop that maintains the timeline of operations, enabling real-time fidelity and traceability.
A digital twin does not operate by replaying logs or feeding historical results into separate analytical layers. It does not rely on externally injected results to approximate behavior, nor does it depend on post-execution stitching to infer state. Visualization overlays and static scenario simulators may present realistic depictions, but they do not satisfy the continuous, authoritative state requirements that distinguish a digital twin.
Endeavor’s architecture was designed to avoid these limitations by integrating all aspects of state, physics, control, and time advancement within a single execution engine.
The inherent value of a digital twin is its continuity and fidelity. By owning state and causality natively, the system can be used for planning, execution rehearsal, real-time shop floor integration, and operational validation without switching contexts. Users can explore “what-if” scenarios, evaluate anomalous conditions, and integrate live data streams while preserving system integrity.
This consistency is central to how Endeavor supports operational decision making, training, and automation workflows.
Single source of truth during execution
The system maintains a continuously evolving source of truth for all physics and operational state. State is owned and resolved within the running engine itself, rather than reconstructed externally or inferred after execution.
No resets, no staged runs
Execution persists without predefined start or stop boundaries. Physics and operational logic advance continuously, allowing outcomes to emerge from prior actions without reinitialization or scenario replay.
Cause and effect resolved in real time
Inputs propagate through the runtime as conditions change, preserving temporal order and physical consistency. Cause-and-effect relationships are resolved inside the running system, not approximated through post-processing or overrides.
Valid across planning, training, and execution
Because state, timing, and causality are resolved within a single engine, the system remains coherent across planning, rehearsal, training, and live integration without reconciliation between tools or models.
Explore how Digital Twins fits within Endeavor’s runtime platform architecture.
For workflows that bridge simulation and live system execution
For workflows that bridge simulation and live system execution
Training, operations, or simulation architecture—start with a focused discussion on requirements and deployment context.