Mohsin R.

I help physical AI companies get the training and validation data their models need: physics-accurate simulation datasets, synthetic data, and engineering ground truth for robotics, drones, and autonomous systems. Most AI teams are strong on models but short on data that reflects real-world physics. That's where we come in. As CEO of InPhoenix, I lead a 25-person engineering team with deep roots in aerospace, CFD, FEA, and UAV systems. We generate data that is physically correct, not just visually plausible. What we deliver: • Large-scale simulation datasets (CFD, structural, flight dynamics) • Synthetic data pipelines for perception and control models • Labeled engineering data and edge-case scenario generation • Physics validation of model outputs against high-fidelity solvers Recent work: generated training data for a physical AI company's foundation models. Tell me what your model needs to learn, and I'll scope a dataset to match.