Niobia Accelerates Chip and Battery Defect Detection

Niobia’s approach centers on localized hardware, mounting AI-equipped GPUs directly onto manufacturing lines to act as high-precision sensors. These agents are trained to detect pinhole-sized flaws, such as surface scratches, while aggregating production data into a single interface. By keeping the AI models self-contained, the startup addresses a primary concern among manufacturers: the protection of proprietary research data. Customers maintain control over their own encryption keys, ensuring that sensitive information never leaves the local environment or enters a public cloud.

Co-founders Gaurav Jha and Harveen Kaur, both chemists with backgrounds in the semiconductor and battery sectors, are targeting three specific manufacturing niches: film coating, electroplating, and fluidized bed reaction. As the company prepares to present at TechCrunch Disrupt 2026, the long-term vision is to move beyond mere diagnostic assistance toward the realization of fully autonomous factories. For now, the startup is focused on solving the high-stakes inefficiencies that plague hardware development, where a single undetected error can derail entire production timelines.