# VLA_ENGINE_v2.0

Intelligence for the
Physical World.

Bridging the Sim-to-Real gap with expert-verified VLA trajectories. We provide the grounding needed for autonomous systems to operate safely in unstructured environments.

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acadify_sys_v4
// Init Emulation Engine: Isaac Sim await> acadify.eval.robotics({ "env": "Warehouse_Navigation_v4", "agent_url": "https://api.model.com/v1/vla" }); > Loading 3D spatial occlusions... [OK] > Synthesizing physics properties... [OK] // Executing Manipulation Harness const> results = await> acadify.eval.runSim(); > Spatial Precision: 98.4%
10K+
Simulated Hours
100%
Physics Verified
7-DOF
Arm Support
VLA
Native Data
CAPABILITIES

Grounded datasets for physical agents.

High-fidelity data needed to train Vision-Language-Action (VLA) models.

VLA Trajectories

Expert-verified trajectories testing spatial reasoning and multi-step manipulation across diverse robotic hardware.

# DATASET: VLA_TRAJ_v1

Sim-to-Real Data

Specialized datasets for domain randomization and transfer learning, ensuring models adapt seamlessly from virtual to physical.

# DATASET: SIM_REAL_L3

Navigation Bench

Pathfinding and obstacle avoidance data in high-density warehouse and domestic simulations with dynamic occlusions.

# DATASET: NAV_BENCH_v4
EVALUATION FRAMEWORKS

Robotics Benchmarks.

Evaluating functional correctness, safety protocols, and operational reliability.

Manipulator-Bench

Testing 7-DOF arm precision, force control, and adaptive grasping across 200+ unique objects.

Spatial-IQ

Measures an agent's ability to interpret and reason about 3D space, occlusions, and dynamic obstacles.

Enterprise Deliverables

  • Kinematic Accuracy Report

    Verified precision metrics for joint manipulation and pathfinding.

  • Collision Safety Audit

    Deep-dive analysis of collision avoidance during dynamic task execution.

SUPPORT

FAQ.

Understanding our rigorous evaluation protocols and data quality standards.

We use domain randomization and physical realism tuning in Isaac Sim, coupled with expert-verified real-world trajectories for seamless transfer.

Our datasets support various form factors including 7-DOF arms, quadrupeds, and mobile manipulators.

Ready to benchmark your models?

Get immediate access to our frontier evaluation frameworks and alignment APIs.

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