From Data to Decisions. Simulate the Future.
Build a full system digital twin for integrated transport and energy operations
GNOS is a cloud-based digital twin and simulation environment used to model, test, and validate how real-world systems perform before construction, commissioning, or operational change.
Rail and road physics engines are combined with agent-based and event-driven simulation in a single environment, allowing engineers or analysts to replicate the physical and operational behaviour of assets, networks, and processes with high fidelity.
Built by engineers and simulation specialists with operational experience across decarbonisation, mining, rail, transport, and processing, the platform captures physical forces, process interactions, and scheduling logic inside a web-based workspace that adapts to each discipline.
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Built for industry. Designed for change.
GNOS uses detailed physics engines, not high level approximations. The physics-based simulation approach ensures digital-twin precision to enable models to replicate actual operational behaviour across rail, road, and mixed transport networks.
Rail
Models traction effort, coupler forces, braking curves, gradients, and regenerative energy to analyse headways, timetable adherence, and network capacity. Calculates longitudinal train dynamics, multi-body interactions, tractive effort, braking curves, and coupler forces between vehicles. Factors in gradient, curvature, resistance, and regenerative braking to reproduce true energy and momentum behaviour under load. Engineers can test timetable changes, track geometry, or rolling stock performance and compare outcomes directly against field data.
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Measure train movements per hour, meet–pass rules, and corridor occupancy to find choke points and test timetable variants.
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Evaluate alternative dispatch strategies, rolling stock mixes, and pathing priorities.
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Quantify effects on headways, punctuality bands, and line capacity with outputs you can compare to recorded runs.
Mining
Simulates haul-vehicle and asset cycles, impact of different ramp profiles, blending operations, and crusher queues to produce accurate throughput and payload data.
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Optimise haul routes against ramp grades, travel times, and queue rules.
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Calibrate shovel–truck–dump cycles, crusher constraints, and stockpile reclaim strategies to hit production targets.
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Model mine-to-port flows end-to-end, balance shift start offsets and equipment schedules, and validate operational changes for throughput, cycle-time variance, fuel or energy use, and unit cost certainty.
Supply chain, logistics and manufacturing
GNOS replicates functionality such as yard flow, berth allocation, crane scheduling, and gate operations to quantify dwell times and utilisation.
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Streamline bulk terminal and warehouse operations by simulating gate-to-gate movements, yard layout options, resource rosters, and berth or crane plans.
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Decarbonisation
Evaluates regeneration, charging and refuelling strategies, battery life, and emissions under multiple operating conditions.
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Powerful network and routing engine for large and small systems
Configure train consist specifications, haul-truck dispatch cycles, and terminal scheduling constraints with accuracy, all in a single digital-twin environment.
GNOS allows engineers to model the entire operational chain from mine to port, yard to rail, or energy generation to consumption using physics-based rail and road engines, agent and event simulation, and validated process logic in one workspace.
Configure your operational network with engineering precision
Define physical parameters and control logic
Define track gradients, pit ramp profiles, and yard flow logic using real geometry, asset data, and control parameters. Every network element, such as locomotive tractive effort, coupler limits, haul-truck payload variance, conveyor speed, or berth allocation, can be configured to match actual operating conditions, providing a measurable foundation for performance analysis.
Test operational scenarios, measure throughput bottlenecks, and quantify energy use across your network with a high level of precision. Engineers can evaluate alternative timetables, fleet sizes, and equipment mixes; simulate unplanned downtime or maintenance windows; and observe how changes ripple across connected systems.
Test and compare operational scenarios
One unified platform to simulate asset dynamics and process flows all under the same roof
Translate complexity into clear insight
For mining and logistics, this means identifying how pit-to-port constraints and yard dwell times affect total export capacity. For rail, it means validating how timetable adjustments, braking strategies, and track speed restrictions influence corridor efficiency. For energy and decarbonisation projects, it means substantiating how charging schedules, rates or locations and battery degradation affect system-wide energy demand and emissions outcomes.
By modelling every dependency within a single environment, GNOS provides a complete system view, allowing teams to test, validate, and optimise performance before it impacts the real network.
Launch scenario runs with distributed compute
Validate outputs against live or historic data
Analyse results to inform operational planning
Getting started has never been easier with GNOS’s cloud first architecture
See GNOS in action.
GNOS includes AI-assisted guidance to accelerate model setup and reduce onboarding time. The integrated assistant supports engineers by automating repetitive configuration tasks and providing real-time, context-aware suggestions during model creation.
Import operational or legacy model data without rebuilding from scratch.
Bring in network geometry, schedules, asset specifications, or existing models from platforms such as AnyLogic, OpenTrack, Simio, Arena, ExtendSim, and more. GNOS supports direct import of structured datasets, preserving model integrity and enabling rapid migration from legacy systems or competitor products. Use existing client data to simulate interdependent activities across assets and processes, providing integrated operational insights.
GNOS AI can:
GNOS includes AI-assisted guidance to accelerate model setup and reduce onboarding time. The integrated assistant supports engineers by automating repetitive configuration tasks and providing real-time, context-aware suggestions during model creation.
Pre-populate common logic patterns to reduce manual setup for processes like signalling, truck dispatch, or resource allocation.
Offer contextual validation hints to identify missing parameters or conflicting logic before simulation runs.
Accelerate overall adoption with:
Faster learning curves so you can be productive sooner
Enables experienced engineers to focus on accurate operational logic, not platform mechanics
Reduces setup errors through guided workflows and best-practice templates
Ensures consistent model construction and validation standards across teams
Web-based execution with distributed compute
GNOS executes complex network simulations directly through a web-based interface, supported by a distributed compute infrastructure. You also don’t need to install software on your local machine, nor will you be limited by system resources when you wait for simulations to finish. This design allows engineers to run detailed digital-twin models, including thousands of agents, multiple rail corridors, or integrated energy systems, without relying on local hardware or sequential desktop processing.
By distributing simulations across multiple servers, GNOS enables parallel execution of large-scale scenarios. Users can launch and compare hundreds of operational variants simultaneously, adjusting schedules, fleet configurations, or energy parameters, and review performance metrics in real time.
Parallel distribution significantly increases processing efficiency for models that traditionally require long sequential runtimes, such as multi-corridor rail networks or combined mining and logistics operations. The result is faster model execution, greater throughput of simulation runs, and improved responsiveness during analysis and decision-making.
GNOS transforms simulation from a workstation-bound process into a scalable, accessible engineering environment, allowing teams to focus on analysis, not hardware limitations. GNOS can also be deployed onto a Client’s network or local machine if desired.
Engineered for transparency, scalability, and verification
Bring in network geometry, schedules, asset specifications, or existing models from platforms such as AnyLogic, OpenTrack, Simio, Arena, ExtendSim, and more. GNOS supports direct import of structured datasets, preserving model integrity and enabling rapid migration from legacy systems or competitor products. Use existing client data to simulate interdependent activities across assets and processes, providing integrated operational insights.
Interface layer
Web-based workspace
Engineers configure models, launch simulations, and analyse results through a browser interface that requires zero installation.
Execution layer
Distributed simulation engines
Data layer
Integration and versioning
Metrics that matter or outcome focused
See what optimises performance, then act on it
Pinpoint where capacity hits its limit
Quantify the cost of delays before they happen
Validate changes with field-comparable data
Build the business case with measurable outcomes
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See how our advanced, cloud‑based simulation helps teams lift throughput, avoid deadlocks, and de‑risk planning across mining, rail, logistics, and ports.