Niobia takes the guesswork out of some of tech’s most expensive mistakes

San Francisco-based startup Niobia is betting big on a critical but often overlooked part of battery and chip making: helping engineers understand how and why things go wrong. Its AI software flags production defects and lets engineers ask a chatbot what caused them, aiming to deliver answers in minutes rather than days.

总部位于旧金山的初创公司 Niobia 正押注于电池和芯片制造中一个关键但常被忽视的环节：帮助工程师理解生产过程中出现问题的原因和方式。其人工智能软件能够标记生产缺陷，并允许工程师通过聊天机器人询问故障原因，旨在将响应时间从几天缩短至几分钟。

How it works (broadly): The company’s customers place AI agents on their production lines to look for defects, then loop in human engineers to work out what might cause a product to fail. The agents run on self-contained GPUs mounted directly on manufacturing equipment, much like a sensor. They can spot pinhole-sized flaws such as scratches. Niobia’s AI also gathers all the data in one place so engineers can ask a chatbot what went wrong and dig deeper into the cause.

其运作方式（概括）：该公司的客户在生产线上部署人工智能代理以查找缺陷，随后由人类工程师介入，分析导致产品故障的原因。这些代理运行在直接安装于制造设备上的独立 GPU 上，类似于传感器。它们能够发现如划痕等针孔大小的瑕疵。Niobia 的人工智能还将所有数据汇总，以便工程师通过聊天机器人查询故障并深入挖掘根本原因。

Speed is so critical because chips and batteries are some of the world’s most important products, while also increasingly in short supply. As manufacturers continue to develop and improve their technologies, things inevitably go awry during research and development. Engineers then spend days or longer figuring out a fix before they can restart production. Each flaw or mistake can prove costly — sometimes running into the millions of dollars — and set back manufacturing timelines.

速度之所以至关重要，是因为芯片和电池是世界上最重要的产品，且供应日益短缺。随着制造商不断开发和改进技术，研发过程中难免会出现问题。工程师通常需要花费数天甚至更长时间来寻找解决方案，才能重启生产。每一个瑕疵或错误都可能代价高昂——有时损失高达数百万美元——并拖延制造进度。

Niobia co-founders Gaurav Jha and Harveen Kaur both have PhDs in chemistry and have worked at chipmakers and battery manufacturers, giving them firsthand experience with the challenges within the industry. In a call ahead of TechCrunch Disrupt 2026, where the company is a Battlefield finalist, Jha explained that while what Niobia does is specialized, it serves a multibillion-dollar market that includes some of the biggest battery and semiconductor makers today.

Niobia 的联合创始人 Gaurav Jha 和 Harveen Kaur 均拥有化学博士学位，并曾在芯片制造商和电池生产商工作，这使他们对行业内的挑战有着第一手的经验。在 TechCrunch Disrupt 2026 大会前夕的一次通话中，作为该赛事决赛入围者的 Jha 解释称，尽管 Niobia 的业务非常专业，但它服务于一个价值数十亿美元的市场，其中包括当今一些最大的电池和半导体制造商。

“It’s extremely niche; maybe people will never know about it,” said Jha, speaking of the battery and chip manufacturing market that his company aims to serve. “But it’s like behind the scenes, this is powering everything… we just don’t see it in the regular world.” “Every product around you, like glasses or shoes, slippers, wallets, and headphones — these processes touch every single part of it,” added Jha.

“这是一个极其细分的领域；也许人们永远不会注意到它，”Jha 在谈到其公司旨在服务的电池和芯片制造市场时说道。“但它就像幕后推手，支撑着一切……只是我们在日常生活中看不到它。”Jha 补充道：“你身边的每一件产品，比如眼镜、鞋子、拖鞋、钱包和耳机——这些制造工艺都与它们的每一个部件息息相关。”

Niobia’s agents run on open source models that the company trains further with battery and chip research and other data. That training is what lets them identify pinhole-sized defects. Jha said that Niobia chose open source models largely because its customers don’t want their highly sensitive company information going into a public AI cloud where it might be used to train the model. “None of our customers want their proprietary data to go to the cloud, even if we tell them it’s safe,” said Jha.

Niobia 的代理运行在开源模型之上，公司利用电池和芯片研究及其他数据对这些模型进行进一步训练。正是这种训练使它们能够识别针孔大小的缺陷。Jha 表示，Niobia 选择开源模型主要是因为客户不希望其高度敏感的公司信息进入可能被用于模型训练的公共人工智能云端。“我们的客户都不希望他们的专有数据上传到云端，即使我们告诉他们那是安全的，”Jha 说。

The startup also outlines how it approaches cybersecurity, given the high-stakes race among adversarial nations to innovate in the battery and chip space. Niobia, for instance, lets its customers hold their own encryption keys so that the startup cannot decrypt the customers’ data. Jha said that the company’s priority for now is to focus on three specialties, such as film coating, electroplating (which is coating a surface with metal using an electric current), and fluidized bed reaction (a chemical process where solid particles are suspended in a gas or liquid).

鉴于各国在电池和芯片领域的高风险创新竞争，这家初创公司还概述了其网络安全方案。例如，Niobia 让客户持有自己的加密密钥，从而确保初创公司本身无法解密客户数据。Jha 表示，公司目前的首要任务是专注于三个专业领域：薄膜涂层、电镀（利用电流在表面覆盖金属）以及流化床反应（一种将固体颗粒悬浮在气体或液体中的化学过程）。

He said that the company also wants its technology to become more autonomous, with the eventual aim of building out a fully self-driving factory for its customers. If you’re curious to learn more, Niobia will present onstage at TechCrunch Disrupt this afternoon in San Francisco. Join us to catch the company and the 19 startups against which it’s competing as part of our storied Startup Battlefield competition, happening today, Tuesday, through Thursday, October 15.

他表示，公司还希望其技术变得更加自主，最终目标是为客户打造完全自动化的工厂。如果您想了解更多信息，Niobia 将于今天下午在旧金山的 TechCrunch Disrupt 大会上进行展示。欢迎加入我们，观看该公司及其竞争对手——另外 19 家初创公司——参与我们久负盛名的 Startup Battlefield 竞赛，活动将于今天（周二）持续至 10 月 15 日（周四）。