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Physical AI Scenario Services Simulation Operations Services

Simulation Operations Services (SimOps)

Run simulation programs like production systems, repeatable, measurable, and scalable.

End-to-end Simulation Operations, delivered as a managed service

DDD’s Simulation Operations services help teams build, operate, and continuously improve large-scale simulation workflows, spanning scenario pipelines, synthetic data, execution operations, and results triage, so engineering and safety teams can move from ad-hoc simulation to disciplined, always-on validation.

Scenario Generation & Mining 

By extracting relevant events, parameterizing behaviors, and curating environment variations, this workflow ensures comprehensive testing across normal, rare, and high-risk conditions. DDD enables scalable scenario creation aligned with perception, prediction, and planning model requirements.
Simulation Orchestration & Test Execution
Our process ensures consistent execution, automated validation, and structured test reporting. DDD supports simulation cycle management, multi-sensor replay, and continuous quality control for high-fidelity AV and robotics testing.
Scenario Enrichment & Parameterization

By adjusting weather, lighting, traffic density, object placement, and edge-case triggers, DDD increases scenario complexity and improves stress-testing coverage for safety-critical AI systems across physical AI domains.

Simulation Data Review & Quality Assurance

Our teams perform frame-by-frame reviews, reality alignment checks, and long-tail event identification. DDD ensures that simulation outputs meet engineering-grade requirements for safe model validation.

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Industries We Support

Autonomous Driving

Supports large-scale simulation of urban, highway, and complex mixed-traffic scenarios for end-to-end autonomy validation.

ADAS

Enhances ADAS reliability with varied real-world and synthetic testing scenarios covering perception, intervention logic, and corner-case behaviors.

Robotics

Provides high-fidelity scenario diversity for navigation, manipulation, and human–robot interaction in dynamic indoor and outdoor environments.

Healthcare Automation

Simulates controlled clinical environments, robotic workflows, and patient interaction scenarios for improved safety and precision.

Agriculture Technology

Generates variable terrain, crop, weather, and machinery scenarios to validate autonomous farm robots and off-road systems.

Humanoids

Creates complex interaction scenarios with realistic human behavior, object manipulation diversity, and unpredictable environmental changes.

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Frequently Asked Questions

What is Simulation Ops, and why is it important?

Simulation Ops refers to the structured creation, orchestration, enrichment, and validation of simulation scenarios used to test AI systems safely and at scale. It accelerates development and improves real-world performance.

What types of data can be used for scenario generation?
DDD works with video, LiDAR, radar, fleet logs, multi-modal sensor outputs, synthetic assets, and event-triggered datasets to create simulation-ready scenarios.
How does Simulation Ops improve model accuracy?
By exposing models to diverse, realistic, edge-case, and parameterized scenarios, Simulation Ops enhances perception, planning, and control robustness.
Can DDD scale simulation workloads for large autonomous programs?
Yes. Our operational workforce and specialized workflows allow us to support continuous scenario production and high-volume simulation QA.
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