Niobia AI Reduces Production Downtime for Chip and Battery Makers

San Francisco-based startup Niobia is introducing an artificial intelligence solution designed to help engineers rapidly diagnose production defects in the manufacturing of semiconductors and batteries. By deploying AI agents directly on factory floors, the company aims to reduce the time spent identifying and resolving production issues from days to mere minutes.

The system utilizes self-contained GPUs mounted onto manufacturing equipment, functioning similarly to sensors. These agents are trained on open-source models supplemented with industry-specific data, enabling them to detect minute flaws, such as pinhole-sized scratches, on production lines. Once a defect is identified, human engineers can interact with a chatbot interface to query the system for root cause analysis, centralizing data that was previously scattered across different stages of production.

The urgency for such speed is driven by the high stakes in chip and battery manufacturing. These components are critical global commodities that are often in short supply. When errors occur during research and development or production, the resulting downtime can cost companies millions of dollars and significantly delay manufacturing timelines.

Niobia was founded by Gaurav Jha and Harveen Kaur, both of whom hold PhDs in chemistry and have extensive experience working at chip and battery manufacturers. Speaking ahead of TechCrunch Disrupt 2026, where the company is a finalist in the Startup Battlefield competition, Jha highlighted the niche but essential nature of their target market.

“It’s extremely niche; maybe people will never know about it,” Jha said. “But it’s like behind the scenes, this is powering everything… we just don’t see it in the regular world.” He noted that the processes involved in chip and battery making underpin a wide range of consumer goods, including eyewear, footwear, wallets, and headphones.

A key differentiator for Niobia is its approach to data security. Recognizing that customers are reluctant to send proprietary information to public cloud-based AI models, the company runs its AI on local hardware. Furthermore, Niobia allows customers to retain their own encryption keys, ensuring that the startup cannot access or decrypt sensitive manufacturing data.

Currently, Niobia is focusing on three specific manufacturing specialties: film coating, electroplating, and fluidized bed reactions. Looking ahead, the company intends to increase the autonomy of its technology, with the long-term goal of enabling fully self-driving factories for its clients.

Niobia is set to present its technology at TechCrunch Disrupt in San Francisco, competing against 19 other startups in the Startup Battlefield series running through October 15.