Physical AI for autonomous robots, fleets, and factory automation
Novus HiTech operates two distinct Physical AI businesses: autonomous mobile robots (AMRs) for manufacturing intralogistics and vision-guided assembly, and an ADAS + driver monitoring platform embedded in commercial vehicles. The stack reveals a dual-track engineering approach — robotics middleware (ROS, ROS 2, Gazebo, Isaac Sim, LiDAR) paired with cloud analytics (AWS, Azure, GCP, Redshift, Snowflake, Grafana, Power BI) — to handle real-world deployment at scale (1,400 robots, 120,000 vehicles, 7 billion kilometres of fleet data). Hiring velocity is accelerating but skews heavily sales (5 roles) over engineering (1 role), suggesting a land-expansion phase rather than platform scaling.
Novus HiTech designs and deploys autonomous robots and AI safety systems for industrial manufacturers and commercial vehicle OEMs. On the factory floor, their AMRs handle smart assembly, intralogistics, and vision-guided operations for customers including Eicher, John Deere, Honda, JCB, Caterpillar, and Mondelez. On the road, their ADAS and driver monitoring platform integrates into 20 active OEM production lines (25 total design wins covering 50% of the commercial vehicle OEM market). The company reports 1,400 robots in field, 120,000 vehicles running their stack, and customer outcomes including 40% reduction in material handling costs and 47% fewer unsafe driving events. Headquartered in Gurgaon with a second office in Indianapolis, Novus HiTech is part of the HiTech Group and has filed 150+ patents since 2005.
Robotics: ROS, ROS 2, Gazebo, Isaac Sim, LiDAR, OPC UA. Cloud/analytics: AWS, Azure, GCP, Redshift, Snowflake, Grafana, Power BI. Core: Python, C++, Docker, Kubernetes. Industrial integrations: Siemens, Mitsubishi Electric, MQTT.
1,400 autonomous mobile robots deployed across manufacturing customers. Additionally, 120,000 commercial vehicles run their ADAS and driver monitoring platform, with 20 OEM programs in active production.
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Novus Hi-Tech's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.