Computer vision and AI for systems that operate in the real world.
Robomous is an engineering company focused on computer vision, perception, machine learning, robotics, and simulation. We solve difficult technical problems and build production systems designed for real operating constraints.
Selected technologies we work with
Engineering for intelligent systems.
We work where perception, machine learning, software, and physical systems meet. Our focus is on engineering problems that require reliable behavior outside a controlled demo.
Computer Vision & Perception
Detection, segmentation, tracking, multimodal perception, 3D vision, and visual inspection systems built around real data and operating constraints.
Physical AI & Robotics
Perception and machine learning for robots and autonomous systems, including sensor integration, closed-loop evaluation, and control-oriented workflows.
Simulation & Synthetic Data
Simulation environments, synthetic data, scenario generation, and sim-to-real workflows for systems that are difficult or expensive to validate in the physical world.
Machine Learning Systems
Training, inference, evaluation, GPU workloads, and the software infrastructure required to move models from experiments into reliable production systems.
From an uncertain problem to a system you can run.
Real AI systems have noisy data, latency, hardware limits, integration constraints, failure modes, and operational requirements. We help teams work through those constraints from early technical exploration to production engineering.
Discuss a technical problemResearch & Prototyping
De-risk new ideas with focused experiments, baselines, prototypes, and measurable technical criteria before committing to a larger build.
Production Engineering
Turn promising models into maintainable software with clear interfaces, observability, deployment paths, performance targets, and failure handling.
Technical Partnership
Work directly with engineers who can reason across models, data, backend systems, simulation, infrastructure, and integration instead of treating each layer as a separate problem.
Research & engineering notes
We write about computer vision, machine learning, robotics, simulation, and the engineering lessons that come from building systems for real operating conditions.
Physical AI: When artificial intelligence leaves the screen and enters the real world
At CES 2026, Jensen Huang said robotics had reached its “ChatGPT moment.” The line resonated because it points to something real, even if the comparison has limits. ChatGPT made technology visible to the public after years of maturing inside research labs. Physical AI presents a different challenge. The hard part is not building a compelling interface. It is solving a far more demanding technical problem.
Set Up Ubuntu Desktop on AWS with Amazon DCV and Nvidia GPU (2024 Guide)
Using the default Ubuntu user account provided in AWS images is not recommendedIn this article, I will guide you step-by-step through the process of installing Ubuntu Desktop on AWS, configuring Nvidia drivers, and enabling the Amazon DCV server. This setup will allow you to access the remote desktop using the DCV client provided by Amazon.